text:
put forward to minimize potential errors. In the present study, we tested a knowledge-based approach that can be combined with any form of registration algorithm. This approach consisted of a library of intermediate images (mediators) with known transformation to the target image. Test images were first registered to all mediators and the best mediator was selected to ensure optimum registration to the target. In order to select the best mediator, we evaluated two similarity criteria: the sum of squared differences and mutual information. This approach was applied to 48 mediators and 96 test images. In order to reduce one of the main drawbacks of the approach, increased computation time, we reduced the size of the library by clustering. Our results indicated clear improvement in registration accuracy.},
author = {Zhang, Xinyuan and Feng, Yanqiu and Chen, Wufan and Li, Xin and Faria, Andreia V. and Feng, Qianjin and Mori, Susumu},
doi = {10.3389/fnins.2019.00909},
issn = {1662453X},
journal = {Frontiers in Neuroscience},
keywords = {MNI space,T1-weighted brain image,dice value,linear registration,mediator selection},
title = {{Linear Registration of Brain MRI Using Knowledge-Based Multiple Intermediator Libraries}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073020740{\&}doi=10.3389{\%}2Ffnins.2019.00909{\&}partnerID=40{\&}md5=eedcc60b9393d11a272628fc4bcf4e67},
volume = {13},
year = {2019}
}
@article{RN842,
abstract = {In case of the complicated anatomical structure of the liver, landmark points on a three dimensional (3D) liver surface is hardly distinguished as corresponding pairs visually and automated landmark placing will be extremely time saving for liver registration. This paper presents a fully automated landmark detection method to register livers on multi-phase computed tomography (CT) images. Edge texture features and Support Vector Machine (SVM) are applied to detect the discriminated landmarks of the liver, including both surface and internal points. Using the information of liver shape, 3D gray level co-occurrence matrix is calculated into texture features, from which the most informatics there features are selected by our optimization algorithm for choosing a sub-set of features from a high dimensional feature set. Then automated landmarks detection begins at scanning surface points on the pre-contrast and portal venous phase images, where positive outputs of the SVM classifier are regarded as initial candidates and final candidates are obtained by eliminating false positives (FPs). Finally, relied on the detected landmarks, thin plate splines (TPS) algorithm is used to register livers. Five surface landmarks, together with internal landmarks of the liver center from every 25 mm slice interval, can be detected automatically with sensitivity of 88.33{\%} and accuracy of 98.5{\%}. Surface-based mean error (SME) is decreased from 3.80 to 2.87 mm on average, while SME value has increased 32.4 and 8.0{\%} on average respectively when comparing with the rigid and B-spline methods. The results demonstrate that edge textures and SVM classifier are effective in the automated landmark detection. Together with TPS algorithm, fully automated liver registration is able to be achieved on multi-phase CT images.},
author = {Zhang, Xuejun and Tan, Xiaomin and Gao, Xin and Wu, Dongbo and Zhou, Xiangrong and Fujita, Hiroshi},
doi = {10.1007/s10586-018-2567-3},
issn = {15737543},
journal = {Cluster Computing},
keywords = {Edge textures,Landmark detection,Liver registration,TPS},
pages = {15305--15319},
title = {{Non-rigid registration of multi-phase liver CT data using fully automated landmark detection and TPS deformation}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044478175{\&}doi=10.1007{\%}2Fs10586-018-2567-3{\&}partnerID=40{\&}md5=43af833a57941962e238b16f43fb845f},
volume = {22},
year = {2019}
}
@article{Li2018,
abstract = {Purpose: The purpose of this study was to enhance the deformation range of demons-based deformable image registration (DIR) for large respiration-induced organ motion in the reconstruction of time-resolved four-dimensional magnetic resonance imaging (TR-4DMRI) for multi-breath motion simulation. Methods: A demons-based DIR algorithm was modified to enhance the deformation range for TR-4DMRI reconstruction using the super-resolution approach. A pseudo demons force was introduced to accelerate the coarse deformation in a multi-resolution (n = 3) DIR approach. The intensity gradient of a voxel was applied to its neighboring (5 × 5 × 5) voxels with a weight of Gaussian probability profile ($\sigma$ = 1 voxel) to extend the demons force, especially on those voxels that have little intensity gradience but high-intensity difference. A digital 4DMRI phantom with 3–8 cm diaphragmatic motions was used for DIR comparison. Six volunteers were scanned with two high-resolution (highR: 2 × 2 × 2 mm3) breath-hold (BH) 3DMR images at full inhalation (BHI) and full exhalation (BHE) and low-resolution (lowR: 5 × 5 × 5 mm3) free-breathing (FB) 3DMR cine images (2 Hz) under an IRB-approved protocol. A cross-consistency check (CCC) (BHI→FB←BHE), with voxel intensity correlation (VIC) and inverse consistency error (ICE), was introduced for cross-verification of TR-4DMRI reconstruction. Results: Using the digital phantom, the maximum deformable magnitude is doubled using the modified DIR from 3 to 6 cm at the diaphragm. In six human subjects, the first 15-iteration DIR using the pseudo force deforms 200 ± 150{\%} more than the original force, and succeeds in all 12 cases, whereas the original demons-based DIR failed in 67{\%} of tested cases. Using the pseudo force, high VIC ({\textgreater}0.9) and small ICE (1.6 ± 0.6 mm) values are observed for DIR of BHI{\&}BHE, BHI→FB, and BHE→FB. The CCC identifies four questionable cases, in which two cases need further DIR refinement, without missing true negative. Conclusions: The introduction of a pseudo demons force enhances the largest deformation magnitude up to 6 cm. The cross-consistency check ensures the quality of TR-4DMRI reconstruction. Further investigation is ongoing to fully characterize TR-4DMRI for potential multi-breathing-cycle radiotherapy simulation.},
author = {Li, Guang and Sun, August and Nie, Xingyu and Moody, Jason and Huang, Kirk and Zhang, Shirong and Sharma, Satyam and Deasy, Joseph},
doi = {10.1002/mp.13179},
issn = {00942405},
journal = {Medical Physics},
keywords = {deformable image registration (DIR),image-guided radiotherapy (IGRT),multi-breath motion assessment,time-resolved four-dimensional magnetic resonance },
month = {nov},
number = {11},
pages = {5197--5207},
publisher = {John Wiley and Sons Ltd.},
title = {{Introduction of a pseudo demons force to enhance deformation range for robust reconstruction of super-resolution time-resolved 4DMRI}},
volume = {45},
year = {2018}
}
@article{Klemm2017,
abstract = {Purpose: Due to rapid developments in the research areas of medical imaging, medical image processing and robotics, computer-assisted interventions (CAI) are becoming an integral part of modern patient care. From a software engineering point of view, these systems are highly complex and research can benefit greatly from reusing software components. This is supported by a number of open-source toolkits for medical imaging and CAI such as the medical imaging interaction toolkit (MITK), the public software library for ultrasound imaging research (PLUS) and 3D Slicer. An independent inter-toolkit communication such as the open image-guided therapy link (OpenIGTLink) can be used to combine the advantages of these toolkits and enable an easier realization of a clinical CAI workflow. Methods: MITK-OpenIGTLink is presented as a network interface within MITK that allows easy to use, asynchronous two-way messaging between MITK and clinical devices or other toolkits. Performance and interoperability tests with MITK-OpenIGTLink were carried out considering the whole CAI workflow from data acquisition over processing to visualization. Results: We present how MITK-OpenIGTLink can be applied in different usage scenarios. In performance tests, tracking data were transmitted with a frame rate of up to 1000 Hz and a latency of 2.81 ms. Transmission of images with typical ultrasound (US) and greyscale high-definition (HD) resolutions of 640 × 480 and 1920 × 1080 is possible at up to 512 and 128 Hz, respectively. Conclusion: With the integration of OpenIGTLink into MITK, this protocol is now supported by all established open-source toolkits in the field. This eases interoperability between MITK and toolkits such as PLUS or 3D Slicer and facilitates cross-toolkit research collaborations. MITK and its submodule MITK-OpenIGTLink are provided open source under a BSD-style licence (http://mitk.org).},
author = {Klemm, Martin and Kirchner, Thomas and Gr{\"{o}}hl, Janek and Cheray, Dominique and Nolden, Marco and Seitel, Alexander and Hoppe, Harald and Maier-Hein, Lena and Franz, Alfred M.},
doi = {10.1007/s11548-016-1488-y},
issn = {18616429},
journal = {International Journal of Computer Assisted Radiology and Surgery},
keywords = {Computer-assisted interventions,Image-guided therapy,Interoperability,MITK,OpenIGTLink,Ultrasound},
month = {mar},
number = {3},
pages = {351--361},
publisher = {Springer Verlag},
title = {{MITK-OpenIGTLink for combining open-source toolkits in real-time computer-assisted interventions}},
volume = {12},
year = {2017}
}
@inproceedings{Yatabe2017,
author = {Yatabe, Marilia and Ruellas, Antonio and Gomes, Liliane and Macron, Lucie and Lopinto, Julia and Paniagua, Beatriz and Budin, Francois and Cevidanes, Lucia},
booktitle = {2017 IADR/AADR/CADR General Session (San Francisco, California) },
title = {{Comparative Study of Three Methods to Compute 3D Craniofacial Angular Measurements}},
url = {https://iadr.abstractarchives.com/abstract/17iags-2636290/comparative-study-of-three-methods-to-compute-3d-craniofacial-angular-measurements},
year = {2017}
}
@article{Sebille2019,
abstract = {Background: Deep brain stimulation of the pedunculopontine nucleus has been performed to treat dopamine-resistant gait and balance disorders in patients with degenerative diseases. The outcomes, however, are variable, which may be the result of the lack of a well-defined anatomical target. Objectives: The objectives of this study were to identify the main neuronal populations of the pedunculopontine and the cuneiform nuclei that compose the human mesencephalic locomotor region and to compare their 3-dimensional distribution with those found in patients with Parkinson's disease and progressive supranuclear palsy. Methods: We used high-field MRI, immunohistochemistry, and in situ hybridization to characterize the distribution of the different cell types, and we developed software to merge all data within a common 3-dimensional space. Results: We found that cholinergic, GABAergic, and glutamatergic neurons comprised the main cell types of the mesencephalic locomotor region, with the peak densities of cholinergic and GABAergic neurons similarly located within the rostral pedunculopontine nucleus. Cholinergic and noncholinergic neuronal losses were homogeneous in the mesencephalic locomotor region of patients, with the peak density of remaining neurons at the same location as in controls. The degree of denervation of the pedunculopontine nucleus was highest in patients with progressive supranuclear palsy, followed by Parkinson's disease patients with falls. Conclusions: The peak density of cholinergic and GABAergic neurons was located similarly within the rostral pedunculopontine nucleus not only in controls but also in pathological cases. The neuronal loss was homogeneously distributed and highest in the pedunculopontine nucleus of patients with falls, which suggests a potential pathophysiological link. {\textcopyright} 2018 International Parkinson and Movement Disorder Society.},
author = {S{\'{e}}bille, Sophie B. and Rolland, Anne Sophie and Faillot, Matthieu and Perez-Garcia, Fernando and Colomb-Clerc, Antoine and Lau, Brian and Dumas, Sylvie and Vidal, Sara Fernandez and Welter, Marie Laure and Francois, Chantal and Bardinet, Eric and Karachi, Carine},
doi = {10.1002/mds.27578},
issn = {15318257},
journal = {Movement Disorders},
keywords = {Gait disorders,Parkinson's disease,cuneiform nucleus,pedunculopontine nucleus,progressive supranuclear palsy},
month = {feb},
number = {2},
pages = {218--227},
title = {{Normal and pathological neuronal distribution of the human mesencephalic locomotor region}},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mds.27578},
volume = {34},
year = {2019}
}
@article{Looney2018,
abstract = {We present a new technique to fully automate the segmentation of an organ from 3D ultrasound (3D-US) volumes, using the placenta as the target organ. Image analysis tools to estimate organ volume do exist but are too time consuming and operator dependant. Fully automating the segmentation process would potentially allow the use of placental volume to screen for increased risk of pregnancy complications. The placenta was segmented from 2,393 first trimester 3D-US volumes using a semiautomated technique. This was quality controlled by three operators to produce the "ground-truth" data set. A fully convolutional neural network (OxNNet) was trained using this ground-truth data set to automatically segment the placenta. OxNNet delivered state-of-the-art automatic segmentation. The effect of training set size on the performance of OxNNet demonstrated the need for large data sets. The clinical utility of placental volume was tested by looking at predictions of small-for-gestational-age babies at term. The receiver-operating characteristics curves demonstrated almost identical results between OxNNet and the ground-truth). Our results demonstrated good similarity to the ground-truth and almost identical clinical results for the prediction of SGA.},
author = {Looney, P{\'{a}}draig and Stevenson, Gordon N. and Nicolaides, Kypros H. and Plasencia, Walter and Molloholli, Malid and Natsis, Stavros and Collins, Sally L.},
doi = {10.1172/jci.insight.120178},
issn = {23793708},
journal = {JCI insight},
keywords = {Diagnostic imaging,Obstetrics/gynecology,Reproductive Biology},
month = {jun},
number = {11},
publisher = {NLM (Medline)},
title = {{Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning}},
volume = {3},
year = {2018}
}
@article{Belmonte2018,
abstract = {Spatial and spatio-temporal model checking techniques have a wide range of application domains, among which large scale distributed systems and signal and image analysis. We explore a new domain, namely (semi-)automatic contouring in Medical Imaging, introducing the tool VoxLogicA which merges the state-of-the-art library of computational imaging algorithms ITK with the unique combination of declarative specification and optimised execution provided by spatial logic model checking. The result is a rapid, logic based analysis development methodology. The analysis of an existing benchmark of medical images for segmentation of brain tumours shows that simple VoxLogicA analysis can reach state-of-the-art accuracy, competing with best-in-class algorithms, with the advantage of explainability and easy replicability. Furthermore, due to a two-orders-of-magnitude speedup compared to the existing general-purpose spatio-temporal model checker topochecker, VoxLogicA enables interactive development of analysis of 3D medical images, which can greatly facilitate the work of professionals in this domain.},
archivePrefix = {arXiv},
arxivId = {1811.05677},
author = {Belmonte, Gina and Ciancia, Vincenzo and Latella, Diego and Massink, Mieke},
doi = {10.1007/978-3-030-17462-0_16},
eprint = {1811.05677},
isbn = {9783030174613},
issn = {16113349},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
keywords = {Closure spaces,Medical Imaging,Model checking,Spatial logics},
month = {nov},
pages = {281--298},
title = {{Voxlogica: A spatial model checker for declarative image analysis}},
url = {http://arxiv.org/abs/1811.05677},
volume = {11427 LNCS},
year = {2019}
}
@article{Oliveira2015,
abstract = {Objective. The aim of the present study was to develop a fully-automated computational solution for computer-aided diagnosis in Parkinson syndrome based on [123I]FP-CIT single photon emission computed tomography (SPECT) images. Approach. A dataset of 654 [123I]FP-CIT SPECT brain images from the Parkinson's Progression Markers Initiative were used. Of these, 445 images were of patients with Parkinson's disease at an early stage and the remainder formed a control group. The images were pre-processed using automated template-based registration followed by the computation of the binding potential at a voxel level. Then, the binding potential images were used for classification, based on the voxel-as-feature approach and using the support vector machines paradigm. Main results. The obtained estimated classification accuracy was 97.86{\%}, the sensitivity was 97.75{\%} and the specificity 98.09{\%}. Significance. The achieved classification accuracy was very high and, in fact, higher than accuracies found in previous studies reported in the literature. In addition, results were obtained on a large dataset of early Parkinson's disease subjects. In summation, the information provided by the developed computational solution potentially supports clinical decision-making in nuclear medicine, using important additional information beyond the commonly used uptake ratios and respective statistical comparisons. (ClinicalTrials.gov Identifier: NCT01141023)},
author = {Oliveira, Francisco P.M. and Castelo-Branco, Miguel},
doi = {10.1088/1741-2560/12/2/026008},
issn = {17412552},
journal = {Journal of Neural Engineering},
keywords = {DaTSCAN,automated image analysis,binding potential,classification},
month = {apr},
number = {2},
publisher = {Institute of Physics Publishing},
title = {{Computer-aided diagnosis of Parkinson's disease based on [123I]FP-CIT SPECT binding potential images, using the voxels-as-features approach and support vector machines}},
volume = {12},
year = {2015}
}
@inproceedings{Paniagua2018,
abstract = {Studies show that cracked teeth are the third most common cause for tooth loss in industrialized countries. If detected early and accurately, patients can retain their teeth for a longer time. Most cracks are not detected early because of the discontinuous symptoms and lack of good diagnostic tools. Currently used imaging modalities like Cone Beam Computed Tomography (CBCT) and intraoral radiography often have low sensitivity and do not show cracks clearly. This paper introduces a novel method that can detect, quantify, and localize cracks automatically in high resolution CBCT (hr-CBCT) scans of teeth using steerable wavelets and learning methods. These initial results were created using hr-CBCT scans of a set of healthy teeth and of teeth with simulated longitudinal cracks. The cracks were simulated using multiple orientations. The crack detection was trained on the most significant wavelet coefficients at each scale using a bagged classifier of Support Vector Machines. Our results show high discriminative specificity and sensitivity of this method. The framework aims to be automatic, reproducible, and open-source. Future work will focus on the clinical validation of the proposed techniques on different types of cracks ex-vivo. We believe that this work will ultimately lead to improved tracking and detection of cracks allowing for longer lasting healthy teeth.},
author = {Paniagua, Beatriz and Shah, Hina and Hernandez-Cerdan, Pablo and Budin, Francois and Chittajallu, Deepak and Walter, Rick and Mol, Andre and Khan, Asma and Vimort, Jean-Baptiste},
booktitle = {Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging},
doi = {10.1117/12.2293603},
editor = {Gimi, Barjor and Krol, Andrzej},
isbn = {9781510616455},
issn = {0277-786X},
month = {mar},
pages = {55},
publisher = {SPIE},
title = {{Automatic quantification framework to detect cracks in teeth}},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10578/2293603/Automatic-quantification-framework-to-detect-cracks-in-teeth/10.1117/12.2293603.full},
volume = {10578},
year = {2018}
}
@inproceedings{Paniagua2019,
author = {Paniagua, Beatriz and Prothero, Jack and Vimort, Jean-Baptiste and Ruellas, Antonio Carlos O. and Marron, James S. and Cevidanes, Lucia and Benavides, Erika and McCormick, Matthew M. and Hernandez-Cerdan, Pablo},
doi = {10.1117/12.2507978},
isbn = {9781510625532},
issn = {0277-786X},
month = {mar},
pages = {42},
publisher = {SPIE-Intl Soc Optical Eng},
title = {{Advanced statistical analysis to classify high dimensionality textural probability-distribution matrices}},
year = {2019}
}
@article{Oliveira2018,
abstract = {Positron emission tomography (PET) neuroimaging with the Pittsburgh Compound{\_}B (PiB) is widely used to assess amyloid plaque burden. Standard quantification approaches normalize PiB-PET by mean cerebellar gray matter uptake. Previous studies suggested similar pons and white-matter uptake in Alzheimer's disease (AD) and healthy controls (HC), but lack exhaustive comparison of normalization across the three regions, with data-driven diagnostic classification. We aimed to compare the impact of distinct reference regions in normalization, measured by data-driven statistical analysis, and correlation with cerebrospinal fluid (CSF) amyloid $\beta$ (A$\beta$) species concentrations. 243 individuals with clinical diagnosis of AD, HC, mild cognitive impairment (MCI) and other dementias, from the Biomarkers for Alzheimer's/Parkinson's Disease (BIOMARKAPD) initiative were included. PiB-PET images and CSF concentrations of A$\beta$38, A$\beta$40 and A$\beta$42 were submitted to classification using support vector machines. Voxel-wise group differences and correlations between normalized PiB-PET images and CSF A$\beta$ concentrations were calculated. Normalization by cerebellar gray matter and pons yielded identical classification accuracy of AD (accuracy-96{\%}, sensitivity-96{\%}, specificity-95{\%}), and significantly higher than A$\beta$ concentrations (best accuracy 91{\%}). Normalization by the white-matter showed decreased extent of statistically significant multivoxel patterns and was the only method not outperforming CSF biomarkers, suggesting statistical inferiority. A$\beta$38 and A$\beta$40 correlated negatively with PiB-PET images normalized by the white-matter, corroborating previous observations of correlations with non-AD-specific subcortical changes in white-matter. In general, when using the pons as reference region, higher voxel-wise group differences and stronger correlation with A$\beta$42, the A$\beta$42/A$\beta$40 or A$\beta$42/A$\beta$38 ratios were found compared to normalization based on cerebellar gray matter.},
author = {Oliveira, Francisco and Leuzy, Antoine and Castelhano, Jo{\~{a}}o and Chiotis, Konstantinos and Hasselbalch, Steen Gregers and Rinne, Juha and Mendon{\c{c}}a, Alexandre and Otto, Markus and Lle{\'{o}}, Alberto and Santana, Isabel and Johansson, Jarkko and Anderl-Straub, Sarah and Arnim, Christine and Beer, Ambros and Blesa, Rafael and Fortea, Juan and Sanna-Kaisa, Herukka and Portelius, Erik and Pannee, Josef and Zetterberg, Henrik and Blennow, Kaj and Moreira, Ana P. and Abrunhosa, Antero and Nordberg, Agneta and Castelo-Branco, Miguel},
doi = {10.1016/j.nicl.2018.08.023},
issn = {22131582},
journal = {NeuroImage: Clinical},
month = {jan},
pages = {603--610},
publisher = {Elsevier Inc.},
title = {{Data driven diagnostic classification in Alzheimer's disease based on different reference regions for normalization of PiB-PET images and correlation with CSF concentrations of A$\beta$ species}},
volume = {20},
year = {2018}
}
@article{Oliveira2018a,
abstract = {Background: Pittsburgh Compound B (PiB) positron emission tomography (PET) is used to visualize in vivo amyloid plaques in the brain. Frequently the PiB examinations are complemented with a fluorodeoxyglucose (FDG) PET scan to further assess neurodegeneration. Objective: Our goal is to identify alternative correlates of FDG images by assessing which kinetic methods originate PiB derived relative delivery ratio (R 1) images that can be correlated with the FDG images, and to compare them with PiB perfusion (pPiB) images obtained from the early-phase of PiB acquisition. Methods: We selected 52 patients with cognitive impairment who underwent a dynamic PiB and FDG acquisitions. To compute the R 1 images, two simplified reference tissue models (SRTM and SRTM2) and two multi-linear reference tissue models (MRTM and MRTM2) were used. The pPiB images were obtained in two different time intervals. Results: All six types of images were of good quality and highly correlated with the FDG images (mean voxelwise within-subjects r {\textgreater} 0.92). The higher correlation was found for FDG-R 1 (MRTM). Regarding the voxelwise regional correlation, the higher mean all brain correlations was r = 0.825 for FDG-R 1 (MRTM) and statistically significant in the whole brain analysis. Conclusion: All R 1 and pPiB images here tested have potential to assess the metabolic impact of neurodegeneration almost as reliably as the FDG images. However, this is not enough to validate these images for a single-subject analysis compared with the FDG image, and thus they cannot yet be used clinically to replace the FDG image before such evaluation.},
author = {Oliveira, Francisco P.M. and Moreira, Ana Paula and {De Mendon{\c{c}}a}, Alexandre and Verdelho, Ana and Xavier, Carolina and Barroca, Dalila and Rio, Joana and Cardoso, Eva and Cruz, {\^{A}}ngela and Abrunhosa, Antero and Castelo-Branco, Miguel},
doi = {10.3233/JAD-180274},
issn = {18758908},
journal = {Journal of Alzheimer's Disease},
keywords = {11 C-PIB,18 F-FDG,Alzheimer's disease,compartmental models,neurodegeneration,perfusion},
number = {1},
pages = {89--97},
publisher = {IOS Press},
title = {{Can 11 C-PiB-PET relative delivery R 1 or 11 C-PiB-PET perfusion replace 18 F-FDG-PET in the assessment of brain neurodegeneration?}},
volume = {65},
year = {2018}
}
@article{Grothausmann2017,
abstract = {The alveolar capillary network (ACN) provides an enormously large surface area that is necessary for pulmonary gas exchange. Changes of the ACN during normal or pathological development or in pulmonary diseases are of great functional impact and warrant further analysis. Due to the complexity of the three-dimensional (3D) architecture of the ACN, 2D approaches are limited in providing a comprehensive impression of the characteristics of the normal ACN or the nature of its alterations. Stereological methods offer a quantitative way to assess the ACN in 3D in terms of capillary volume, surface area, or number but lack a 3D visualization to interpret the data. Hence, the necessity to visualize the ACN in 3D and to correlate this with data from the same set of data arises. Such an approach requires a large sample volume combined with a high resolution. Here, we present a technically simple and cost-efficient approach to create 3D representations of lung tissue ranging from bronchioles over alveolar ducts and alveoli up to the ACN from more than 1 mm sample extent to a resolution of less than 1 $\mu$m. The method is based on automated image acquisition of serially sectioned epoxy resin-embedded lung tissue fixed by vascular perfusion and subsequent automated digital reconstruction and analysis of the 3D data. This efficient method may help to better understand mechanisms of vascular development and pathology of the lung.},
author = {Grothausmann, Roman and Knudsen, Lars and Ochs, Matthias and M{\"{u}}hlfeld, Christian},
doi = {10.1152/ajplung.00326.2016},
issn = {15221504},
journal = {American Journal of Physiology - Lung Cellular and Molecular Physiology},
keywords = {3D reconstruction,Alveolar capillary network (ACN),Stacked histological slices,Virtual endoscopy},
month = {feb},
number = {2},
pages = {L243--L257},
title = {{Digital 3D reconstructions using histological serial sections of lung tissue including the alveolar capillary network}},
url = {https://www.physiology.org/doi/10.1152/ajplung.00326.2016},
volume = {312},
year = {2017}
}
@inproceedings{Grothausmann2018,
abstract = {Changes in lung volume during the breathing cycle and also lung diseases are likely to deform even the smallest airspace units, the alveoli. This study reports general ideas to investigate such changes with 3D digital image processing. It comprises morphological characterizations like volume and surface, an evaluation of the angle distribution between facets formed by the septal walls, the number of neighboring alveoli and a shape analysis of the alveolar airspace. The software used is open-source and custom programs are available at: http://github.com/romangrothausmann/.},
author = {Grothausmann, Roman and M{\"{u}}hlfeld, Christian and Ochs, Matthias and Knudsen, Lars},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-030-04747-4_5},
isbn = {9783030047467},
issn = {16113349},
pages = {49--64},
publisher = {Springer Verlag},
title = {{Shape and Facet Analyses of Alveolar Airspaces of the Lung}},
volume = {11167 LNCS},
year = {2018}
}
@article{Herrmann2018,
abstract = {Background: Digital Imaging and Communications in Medicine (DICOM{\textregistered}) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network. Methods: We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software. Results: Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed. Conclusion: Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.},
author = {Herrmann, Markus D. and Clunie, David A. and Fedorov, Andriy and Doyle, Sean W. and Pieper, Steven and Klepeis, Veronica and Le, Long P. and Mutter, George L. and Milstone, David S. and Schultz, Thomas J. and Kikinis, Ron and Kotecha, Gopal K. and Hwang, David H. and Andriole, Katherine P. and {John Iafrate}, A. and Brink, James A. and Boland, Giles W. and Dreyer, Keith J. and Michalski, Mark and Golden, Jeffrey A. and Louis, David N. and Lennerz, Jochen K.},
doi = {10.4103/jpi.jpi_42_18},
issn = {21533539},
journal = {Journal of Pathology Informatics},
keywords = {Computational pathology,DICOMweb,Image compression,Slide scanning,Whole slide imaging},
month = {jan},
number = {1},
pmid = {30533276},
publisher = {Wolters Kluwer Medknow Publications},
title = {{Implementing the DICOM standard for digital pathology}},
volume = {9},
year = {2018}
}
@article{Malkasian2018,
abstract = {Background: As combined morphological and physiological assessment of coronary artery disease (CAD) is necessary to reliably resolve CAD severity, the objective of this study was to validate an automated minimum-cost path assignment (MCP) technique which enables accurate, vessel-specific assignment of the left (LCA) and right (RCA) coronary perfusion territories using computed tomography (CT) angiography data for both left and right ventricles. Methods: Six swine were used to validate the MCP technique. In each swine, a dynamic acquisition comprised of twenty consecutive volume scans was acquired with a 320-slice CT scanner following peripheral injection of contrast material. From this acquisition the MCP technique was used to automatically assign LCA and RCA perfusion territories for the left and right ventricles, independently. Each animal underwent another dynamic CT acquisition following direct injection of contrast material into the LCA or RCA. Using this acquisition, reference standard LCA and RCA perfusion territories were isolated from the myocardial blush. The accuracy of the MCP technique was evaluated by quantitatively comparing the MCP-derived LCA and RCA perfusion territories to these reference standard territories. Results: All MCP perfusion territory masses (MassMCP) and all reference standard perfusion territory masses (MassRS) in the left ventricle were related by MassMCP = 0.99MassRS+0.35 g (r = 1.00). MassMCP and MassRS in the right ventricle were related by MassMCP = 0.94MassRS+0.39 g (r = 0.96). Conclusion: The MCP technique was validated in a swine animal model and has the potential to be used for accurate, vessel-specific assignment of LCA and RCA perfusion territories in both the left and right ventricular myocardium using CT angiography data. In order to provide a comprehensive morphological and physiological cardiac imaging datasets, the minimum-cost path assignment (MCP) method has been validated, using a swine animal model and computed tomography (CT) imaging. MCP has been shown to accurately quantify left and right coronary artery perfusion territories in the left ventricle, right ventricle and whole heart. The MCP technique provides clinicians and researchers in cardiovascular imaging with a means to accurately and automatically determine coronary-specific perfusion territories in the left and right heart, and could also be used to assess myocardium at-risk distal to a stenosis.},
author = {Malkasian, Shant and Hubbard, Logan and Dertli, Brian and Kwon, Jungnam and Molloi, Sabee},
doi = {10.1016/j.jcct.2018.06.006},
issn = {1876861X},
journal = {Journal of Cardiovascular Computed Tomography},
keywords = {Angiography,Cardiovascular disease,Computerized tomography,Coronary artery disease,Imaging,Myocardium},
month = {sep},
number = {5},
pages = {425--435},
publisher = {Elsevier Inc.},
title = {{Quantification of vessel-specific coronary perfusion territories using minimum-cost path assignment and computed tomography angiography: Validation in a swine model}},
volume = {12},
year = {2018}
}
@article{HadjHamou2016,
abstract = {We propose and detail a deformation-based morphometry computational framework, called Longitudinal Log-Demons Framework (LLDF), to estimate the longitudinal brain deformations from image data series, transport them in a common space and perform statistical group-wise analyses. It is based on freely available software and tools, and consists of three main steps: (i) Pre-processing, (ii) Position correction, and (iii) Non-linear deformation analysis. It is based on the LCC log-Demons non-linear symmetric diffeomorphic registration algorithm with an additional modulation of the similarity term using a confidence mask to increase the robustness with respect to brain boundary intensity artifacts. The pipeline is exemplified on the longitudinal Open Access Series of Imaging Studies (OASIS) database and all the parameters values are given so that the study can be reproduced. We investigate the group-wise differences between the patients with Alzheimer's disease and the healthy control group, and show that the proposed pipeline increases the sensitivity with no decrease in the specificity of the statistical study done on the longitudinal deformations.},
author = {Hadj-Hamou, Mehdi and Lorenzi, Marco and Ayache, Nicholas and Pennec, Xavier},
doi = {10.3389/fnins.2016.00236},
issn = {1662453X},
journal = {Frontiers in Neuroscience},
keywords = {Deformation-based morphometry,Diffeomorphism parametrized by stationary velocity,Longitudinal study,Non-linear registration,Reproducible research,Statistical analysis},
month = {jun},
number = {JUN},
publisher = {Frontiers Research Foundation},
title = {{Longitudinal analysis of image time series with diffeomorphic deformations: A computational framework based on stationary velocity fields}},
volume = {10},
year = {2016}
}
@article{Abbasi2017,
abstract = {Brain tumor pathology is one of the most common mortality issues considered as an essential priority for health care societies. Accurate diagnosis of the type of disorder is crucial to make a plan for remedy that can minimize the deadly results. The main purpose of segmentation and detection is to make distinction between different regions of the brain. Besides accuracy, these techniques should be implemented quickly. In this paper an automatic method for brain tumor detection in 3D images has been proposed. In the first step, the bias field correction and histogram matching are used for pre-processing of the images. In the next step, the region of interest is identified and separated from the background of the Flair image. Local binary pattern in three orthogonal planes (LBP-TOP) and histogram of orientation gradients (HOG-TOP) are used as the learning features. Since 3D images are used in this research we use the idea of in local binary pattern in three orthogonal planes in order to extend histogram orientation gradients for 3D images. The random forest is then used to segment tumorous regions. We evaluate the performance of our algorithm on glioma images from BRATS 2013. Our experimental results and analyses indicate that our proposed framework is superior in detecting brain tumors in comparison with other techniques.},
author = {Abbasi, Solmaz and Tajeripour, Farshad},
doi = {10.1016/j.neucom.2016.09.051},
issn = {18728286},
journal = {Neurocomputing},
keywords = {Histogram orientation gradient,Local binary patterns,MRI images,Medical image processing,Tumor detection},
pages = {526--535},
title = {{Detection of brain tumor in 3D MRI images using local binary patterns and histogram orientation gradient}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {219},
year = {2017}
}
@incollection{Achim2018,
abstract = {The method described here aims at the construction of a single-cell resolution gene expression atlas for an animal or tissue, combining in situ hybridization (ISH) and single-cell mRNA-sequencing (scRNAseq). A high resolution and medium-coverage gene expression atlas of an animal or tissue of interest can be obtained by performing a series of ISH experiments, followed by a process of image registration and gene expression averaging. Using the overlapping fraction of the genes, concomitantly obtained scRNAseq data can be fitted into the spatial context of the gene expression atlas, complementing the coverage by genes.},
author = {Achim, Kaia and Vergara, Hernando Mart{\'{i}}nez and Pettit, Jean Baptiste},
booktitle = {Methods in Molecular Biology},
doi = {10.1007/978-1-4939-7213-5_7},
issn = {10643745},
keywords = {Gene expression,Image registration,Single-cell mRNA-seq,Spatial transcriptomics},
pages = {111--125},
title = {{Spatial transcriptomics: Constructing a single-cell resolution transcriptome-wide expression atlas}},
type = {Serial},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033693516{\&}doi=10.1007{\%}2F978-1-4939-7213-5{\_}7{\&}partnerID=40{\&}md5=697ad0e6f4701bd81a55352e26ae2fbb},
volume = {1649},
year = {2018}
}
@article{Achterberg2016,
abstract = {With the increasing number of datasets encountered in imaging studies, the increasing complexity of processing workflows, and a growing awareness for data stewardship, there is a need for managed, automated workflows. In this paper, we introduce Fastr, an automated workflow engine with support for advanced data flows. Fastr has built-in data provenance for recording processing trails and ensuring reproducible results. The extensible plugin-based design allows the system to interface with virtually any image archive and processing infrastructure. This workflow engine is designed to consolidate quantitative imaging biomarker pipelines in order to enable easy application to new data.},
author = {Achterberg, Hakim C. and Koek, Marcel and Niessen, Wiro J.},
doi = {10.3389/fict.2016.00015},
issn = {2297198X},
journal = {Frontiers in ICT},
keywords = {Data flow,Data processing,Distributed computing,Pipeline,Provenance,Python,Reproducible research,Workflow},
number = {AUG},
title = {{Fastr: A Workflow engine for advanced data flows in medical image analysis}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048206888{\&}doi=10.3389{\%}2Ffict.2016.00015{\&}partnerID=40{\&}md5=453da670107b4919c49586ea9b393a99},
volume = {3},
year = {2016}
}
@article{Acosta2017,
abstract = {Background and purpose Segmentation of intra-prostatic urethra for dose assessment from planning CT may help explaining urinary toxicity in prostate cancer radiotherapy. This work sought to: i) propose an automatic method for urethra segmentation in CT, ii) compare it with previously proposed surrogate models and iii) quantify the dose received by the urethra in patients treated with IMRT. Materials and methods A weighted multi-atlas-based urethra segmentation method was devised from a training data set of 55 CT scans of patients receiving brachytherapy with visible urinary catheters. Leave-one-out cross validation was performed to quantify the error between the urethra segmentation and the catheter ground truth with two scores: the centerlines distance (CLD) and the percentage of centerline within a certain distance from the catheter (PWR). The segmentation method was then applied to a second test data set of 95 prostate cancer patients having received 78 Gy IMRT to quantify dose to the urethra. Results Mean CLD was 3.25 ± 1.2 mm for the whole urethra and 3.7 ± 1.7 mm, 2.52 ± 1.5 mm, and 3.01 ± 1.7 mm for the top, middle, and bottom thirds, respectively. In average, 53{\%} of the segmented centerlines were within a radius {\textless} 3.5 mm from the centerline ground truth and 83{\%} in a radius {\textless} 5 mm. The proposed method outperformed existing surrogate models. In IMRT, urethra DVH was significantly higher than prostate DVH from V74 Gy to V79 Gy. Conclusion A multi-atlas-based segmentation method was proposed enabling assessment of the dose within the prostatic urethra.},
author = {Acosta, Oscar and Mylona, Eugenia and {Le Dain}, Mathieu and Voisin, Camille and Lizee, Thibaut and Rigaud, Bastien and Lafond, Carolina and Gnep, Khemara and de Crevoisier, Renaud},
doi = {10.1016/j.radonc.2017.09.015},
issn = {18790887},
journal = {Radiotherapy and Oncology},
keywords = {Atlas-based segmentation,Dose computation,Prostate cancer radiotherapy,Urethra segmentation,Urinary toxicity},
number = {3},
pages = {492--499},
title = {{Multi-atlas-based segmentation of prostatic urethra from planning CT imaging to quantify dose distribution in prostate cancer radiotherapy}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {125},
year = {2017}
}
@article{Adebar2014,
abstract = {Robotic needle steering systems have the potential to greatly improve medical interventions, but they require new methods for medical image guidance. Three-dimensional (3-D) ultrasound is a widely available, low-cost imaging modality that may be used to provide real-time feedback to needle steering robots. Unfortunately, the poor visibility of steerable needles in standard grayscale ultrasound makes automatic segmentation of the needles impractical. A new imaging approach is proposed, in which high-frequency vibration of a steerable needle makes it visible in ultrasound Doppler images. Experiments demonstrate that segmentation from this Doppler data is accurate to within 1-2 mm. An image-guided control algorithm that incorporates the segmentation data as feedback is also described. In experimental tests in ex vivo bovine liver tissue, a robotic needle steering system implementing this control scheme was able to consistently steer a needle tip to a simulated target with an average error of 1.57 mm. Implementation of 3-D ultrasound-guided needle steering in biological tissue represents a significant step toward the clinical application of robotic needle steering.},
author = {Adebar, Troy K. and Fletcher, Ashley E. and Okamura, Allison M.},
doi = {10.1109/TBME.2014.2334309},
issn = {15582531},
journal = {IEEE Transactions on Biomedical Engineering},
keywords = {Image-guided intervention,robotic needle steering,ultrasound Doppler,ultrasound imaging},
number = {12},
pages = {2899--2910},
title = {{3-D ultrasound-guided robotic needle steering in biological tissue}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {61},
year = {2014}
}
@article{Adluru2007,
abstract = {Dynamic contrast-enhanced (DCE) MRI is a powerful technique to probe an area of interest in the body. Here a temporally constrained reconstruction (TCR) technique that requires less k-space data over time to obtain good-quality reconstructed images is proposed. This approach can be used to improve the spatial or temporal resolution, or increase the coverage of the object of interest. The method jointly reconstructs the space-time data iteratively with a temporal constraint in order to resolve aliasing. The method was implemented and its feasibility tested on DCE myocardial perfusion data with little or no motion. The results obtained from sparse k-space data using the TCR method were compared with results obtained with a sliding-window (SW) method and from full data using the standard inverse Fourier transform (IFT) reconstruction. Acceleration factors of 5 (R = 5) were achieved without a significant loss in image quality. Mean improvements of 28 ± 4{\%} in the signal-to-noise ratio (SNR) and 14 ± 4{\%} in the contrast-to-noise ratio (CNR) were observed in the images reconstructed using the TCR method on sparse data (R = 5) compared to the standard I FT reconstructions from full data for the perfusion datasets. The method has the potential to improve dynamic myocardial perfusion imaging and also to reconstruct other sparse dynamic MR acquisitions. {\textcopyright} 2007 Wiley-Liss, Inc.},
author = {Adluru, Ganesh and Awate, Suyash P. and Tasdizen, Tolga and Whitaker, Ross T. and DiBella, Edward V.R.},
doi = {10.1002/mrm.21248},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {Cardiac perfusion,Dynamic contrast-enhanced MR,L-curve,Regularization,Regularization parameter},
number = {6},
pages = {1027--1036},
title = {{Temporally constrained reconstruction of dynamic cardiac perfusion MRI}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {57},
year = {2007}
}
@article{Ai2019,
abstract = {Since the honeybee possesses eusociality, advanced learning, memory ability, and information sharing through the use of various pheromones and sophisticated symbol communication (i.e., the “waggle dance”), this remarkable social animal has been one of the model symbolic animals for biological studies, animal ecology, ethology, and neuroethology. Karl von Frisch discovered the meanings of the waggle dance and called the communication a “dance language.” Subsequent to this discovery, it has been extensively studied how effectively recruits translate the code in the dance to reach the advertised destination and how the waggle dance information conflicts with the information based on their own foraging experience. The dance followers, mostly foragers, detect and interact with the waggle dancer, and are finally recruited to the food source. In this review, we summarize the current state of knowledge on the neural processing underlying this fascinating behavior.},
author = {Ai, Hiroyuki and Okada, Ryuichi and Sakura, Midori and Wachtler, Thomas and Ikeno, Hidetoshi},
doi = {10.3390/insects10100336},
issn = {20754450},
journal = {Insects},
keywords = {Antenna-mechanosensory center,Brain,Computational analysis,Distance information,Honeybee,Polarized light processing,Sensory processing,Standard brain,Vibration,Waggle dance},
number = {10},
pages = {16},
title = {{Neuroethology of the waggle dance: How followers interact with the waggle dancer and detect spatial information}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {10},
year = {2019}
}
@article{Akbarzadeh2013,
abstract = {Objective: Hybrid PET/MRI presents many advantages in comparison with its counterpart PET/CT in terms of improved soft-tissue contrast, decrease in radiation exposure, and truly simultaneous and multi-parametric imaging capabilities. However, the lack of well-established methodology for MR-based attenuation correction is hampering further development and wider acceptance of this technology. We assess the impact of ignoring bone attenuation and using different tissue classes for generation of the attenuation map on the accuracy of attenuation correction of PET data. Methods: This work was performed using simulation studies based on the XCAT phantom and clinical input data. For the latter, PET and CT images of patients were used as input for the analytic simulation model using realistic activity distributions where CT-based attenuation correction was utilized as reference for comparison. For both phantom and clinical studies, the reference attenuation map was classified into various numbers of tissue classes to produce three (air, soft tissue and lung), four (air, lungs, soft tissue and cortical bones) and five (air, lungs, soft tissue, cortical bones and spongeous bones) class attenuation maps. Results: The phantom studies demonstrated that ignoring bone increases the relative error by up to 6.8 {\%} in the body and up to 31.0 {\%} for bony regions. Likewise, the simulated clinical studies showed that the mean relative error reached 15 {\%} for lesions located in the body and 30.7 {\%} for lesions located in bones, when neglecting bones. These results demonstrate an underestimation of about 30 {\%} of tracer uptake when neglecting bone, which in turn imposes substantial loss of quantitative accuracy for PET images produced by hybrid PET/MRI systems. Conclusion: Considering bones in the attenuation map will considerably improve the accuracy of MR-guided attenuation correction in hybrid PET/MR to enable quantitative PET imaging on hybrid PET/MR technologies. {\textcopyright} 2012 The Japanese Society of Nuclear Medicine.},
author = {Akbarzadeh, A. and Ay, M. R. and Ahmadian, A. and {Riahi Alam}, N. and Zaidi, H.},
doi = {10.1007/s12149-012-0667-3},
issn = {09147187},
journal = {Annals of Nuclear Medicine},
keywords = {Attenuation correction,PET/CT,PET/MRI,Quantification,Tissue classification},
number = {2},
pages = {152--162},
title = {{MRI-guided attenuation correction in whole-body PET/MR: Assessment of the effect of bone attenuation}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {27},
year = {2013}
}
@article{Akbarzadeh2013a,
abstract = {Multimodality image registration plays a crucial role in various clinical and research applications. The aim of this study is to present an optimized MR to CT whole-body deformable image registration algorithm and its validation using clinical studies. A 3D intermodality registration technique based on B-spline transformation was performed using optimized parameters of the elastix package based on the Insight Toolkit (ITK) framework. Twenty-eight (17 male and 11 female) clinical studies were used in this work. The registration was evaluated using anatomical landmarks and segmented organs. In addition to 16 anatomical landmarks, three key organs (brain, lungs, and kidneys) and the entire body volume were segmented for evaluation. Several parameters - such as the Euclidean distance between anatomical landmarks, target overlap, Dice and Jaccard coefficients, false positives and false negatives, volume similarity, distance error, and Hausdorff distance - were calculated to quantify the quality of the registration algorithm. Dice coefficients for the majority of patients ({\textgreater} 75{\%}) were in the 0.8-1 range for the whole body, brain, and lungs, which satisfies the criteria to achieve excellent alignment. On the other hand, for kidneys, Dice coefficients for volumes of 25{\%} of the patients meet excellent volume agreement requirement, while the majority of patients satisfy good agreement criteria ({\textgreater} 0.6). For all patients, the distance error was in 0-10 mm range for all segmented organs. In summary, we optimized and evaluated the accuracy of an MR to CT deformable registration algorithm. The registered images constitute a useful 3D whole-body MR-CT atlas suitable for the development and evaluation of novel MR-guided attenuation correction procedures on hybrid PET-MR systems.},
author = {Akbarzadeh, A. and Gutierrez, D. and Baskin, A. and Ay, M. R. and Ahmadian, A. and {Riahi Alam}, N. and L{\"{o}}vblad, K. O. and Zaidi, H.},
doi = {10.1120/jacmp.v14i4.4163},
issn = {15269914},
journal = {Journal of Applied Clinical Medical Physics},
keywords = {Attenuationcorrection,Deformable model,Image registration,PET/CT,PET/MRI},
number = {4},
pages = {238--253},
title = {{Evaluation of whole-body mr to ct deformable image registration}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {14},
year = {2013}
}
@article{Aksenov2014,
abstract = {Purpose: The local injection of neurotransmitter agonists and antagonists to modulate recorded neurons in awake animals has long been an important and widely used technique in neuroscience. Combined with functional magnetic resonance imaging (fMRI) and simultaneous electrophysiology, local injection enables the study of specific brain regions under precise modulations of their neuronal activity. However, localized injections are often accompanied by mechanical displacement of the tissue, known as volume effect (VE), which can induce changes in electrophysiological recordings as well as artifacts that are particular to fMRI studies. Methods: We characterize the changes produced by VE in an agarose phantom as well as during stimulus-evoked and resting-state fMRI and simultaneously acquired electrophysiology in awake rabbits. Results: Our results demonstrate that localized injection can produce significant intensity changes in fMRI data, even while effects on electrophysiological recordings are minimized. These changes are localized to the vicinity of the injection needle and diminish over time due to diffusion of the injected volume. Conclusion: Sufficient time should be allowed for drug diffusion to ensure stable results, particularly for resting-state fMRI experiments.},
author = {Aksenov, Daniil P. and Li, Limin and Iordanescu, Gheorghe and Miller, Michael J. and Wyrwicz, Alice M.},
doi = {10.1002/mrm.24996},
issn = {15222594},
journal = {Magnetic Resonance in Medicine},
keywords = {ACSF,Brain,Injection,Single unit,Volume effect,fMRI},
number = {4},
pages = {1170--1175},
pmid = {24273205},
title = {{Volume effect of localized injection in functional MRI and electrophysiology}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {72},
year = {2014}
}
@article{Aksenov2016,
abstract = {The adaptation of neuronal responses to stimulation, in which a peak transient response is followed by a sustained plateau, has been well-studied. The blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal has also been shown to exhibit adaptation on a longer time scale. However, some regions such as the visual and auditory cortices exhibit significant BOLD adaptation, whereas other such as the whisker barrel cortex may not adapt. In the sensory cortex a combination of thalamic inputs and intracortical activity drives hemodynamic changes, although the relative contributions of these components are not entirely understood. The aim of this study is to assess the role of thalamic inputs vs. intracortical processing in shaping BOLD adaptation during stimulation in the somatosensory cortex. Using simultaneous fMRI and electrophysiology in awake rabbits, we measured BOLD, local field potentials (LFPs), single- and multi-unit activity in the cortex during whisker and optogenetic stimulation. This design allowed us to compare BOLD and haemodynamic responses during activation of the normal thalamocortical sensory pathway (i.e., both inputs and intracortical activity) vs. the direct optical activation of intracortical circuitry alone. Our findings show that whereas LFP and multi-unit (MUA) responses adapted, neither optogenetic nor sensory stimulation produced significant BOLD adaptation. We observed for both paradigms a variety of excitatory and inhibitory single unit responses. We conclude that sensory feed-forward thalamic inputs are not primarily responsible for shaping BOLD adaptation to stimuli; but the single-unit results point to a role in this behaviour for specific excitatory and inhibitory neuronal sub-populations, which may not correlate with aggregate neuronal activity.},
author = {Aksenov, Daniil P. and Li, Limin and Miller, Michael J. and Wyrwicz, Alice M.},
doi = {10.1111/ejn.13384},
issn = {14609568},
journal = {European Journal of Neuroscience},
keywords = {functional magnetic resonance imaging,neural activity,rabbit,whisker barrel cortex},
number = {9},
pages = {2722--2729},
title = {{Blood oxygenation level dependent signal and neuronal adaptation to optogenetic and sensory stimulation in somatosensory cortex in awake animals}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {44},
year = {2016}
}
@article{Aksenov2016a,
abstract = {Millions of children undergo general anesthesia each year in the USA alone, and a growing body of literature from animals and humans suggests that exposure to anesthesia at an early age can impact neuronal development, leading to learning and memory impairments later in childhood. Although a number of studies have reported behavioral and structural effects of anesthesia exposure during infancy, the functional manifestation of these changes has not been previous examined. In this study we used BOLD fMRI to measure the functional response to stimulation in the whisker barrel cortex of awake rabbits before and after learning a trace eyeblink classical conditioning paradigm. The functional changes, in terms of activated volume and time course, in rabbits exposed to isoflurane anesthesia during infancy was compared to unanesthetized controls when both groups reached young adulthood. Our findings show that whereas both groups exhibited decreased BOLD response duration after learning, the anesthesia-exposed group also showed a decrease in BOLD response volume in the whisker barrel cortex, particularly in the deeper infragranular layer. These results suggest that anesthesia exposure during infancy may affect the intracortical processes that mediate learning-related plasticity.},
author = {Aksenov, Daniil P. and Miller, Michael J. and Li, Limin and Wyrwicz, Alice M.},
doi = {10.1016/j.physbeh.2016.08.030},
issn = {1873507X},
journal = {Physiology and Behavior},
keywords = {Anesthesia,Infant,Learning},
pages = {10--15},
title = {{Eyeblink classical conditioning and BOLD fMRI of anesthesia-induced changes in the developing brain}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {167},
year = {2016}
}
@article{Allan2012,
abstract = {Data-intensive research depends on tools that manage multidimensional, heterogeneous datasets. We built OME Remote Objects (OMERO), a software platform that enables access to and use of a wide range of biological data. OMERO uses a server-based middleware application to provide a unified interface for images, matrices and tables. OMERO's design and flexibility have enabled its use for light-microscopy, high-content-screening, electron-microscopy and even non-image-genotype data. OMERO is open-source software, available at http://openmicroscopy.org/. {\textcopyright} 2012 Nature America, Inc. All rights reserved.},
author = {Allan, Chris and Burel, Jean Marie and Moore, Josh and Blackburn, Colin and Linkert, Melissa and Loynton, Scott and MacDonald, Donald and Moore, William J. and Neves, Carlos and Patterson, Andrew and Porter, Michael and Tarkowska, Aleksandra and Loranger, Brian and Avondo, Jerome and Lagerstedt, Ingvar and Lianas, Luca and Leo, Simone and Hands, Katherine and Hay, Ron T. and Patwardhan, Ardan and Best, Christoph and Kleywegt, Gerard J. and Zanetti, Gianluigi and Swedlow, Jason R.},
doi = {10.1038/nmeth.1896},
issn = {15487091},
journal = {Nature Methods},
number = {3},
pages = {245--253},
title = {{OMERO: Flexible, model-driven data management for experimental biology}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {9},
year = {2012}
}
@inproceedings{Alvarez,
abstract = {We introduce a morphological approach to curve evolution. The differential operators used in the standard PDE snake models can be approached using morphological operations on a binary level set. By combining the morphological operators associated to the PDE components we achieve a new snakes evolution algorithm. This new solution is based on numerical methods which are very simple, fast and stable. Moreover, since the level set is just a binary piecewise constant function, this approach does not require to estimate a contour distance function. To illustrate the results obtained we present some numerical experiments on real images. {\textcopyright}2010 IEEE.},
author = {{\'{A}}lvarez, Luis and Baumela, Luis and Henr{\'{i}}quez, Pedro and M{\'{a}}rquez-Neila, Pablo},
booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
doi = {10.1109/CVPR.2010.5539900},
isbn = {9781424469840},
issn = {10636919},
pages = {2197--2202},
title = {{Morphological snakes}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955987357{\&}doi=10.1109{\%}2FCVPR.2010.5539900{\&}partnerID=40{\&}md5=15e7390806889a59ec5c0fa284c87850},
year = {2010}
}
@article{Anderson2010,
abstract = {Applying Python to a neuroscience project let developers put complex data processing and advanced visualization techniques together in a coherent framework. {\textcopyright} 2006 IEEE.},
author = {Anderson, Erik W. and Preston, Gilbert A. and Silva, Claudio T.},
doi = {10.1109/MCSE.2010.91},
issn = {15219615},
journal = {Computing in Science and Engineering},
keywords = {Brain,Data visualization,Electroencephalography,Libraries,Magnetic resonance imaging,Python,Sensors,Signal processing,Time frequency analysis,Visualization},
number = {4},
pages = {90--95},
title = {{Using python for signal processing and visualization}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {12},
year = {2010}
}
@article{Arabi2016,
abstract = {Quantitative whole-body PET/MR imaging is challenged by the lack of accurate and robust strategies for attenuation correction. In this work, a new pseudo-CT generation approach, referred to as sorted atlas pseudo-CT (SAP), is proposed for accurate extraction of bones and estimation of lung attenuation properties. This approach improves the Gaussian process regression (GPR) kernel proposed by Hofmann et al. which relies on the information provided by a co-registered atlas (CT and MRI) using a GPR kernel to predict the distribution of attenuation coefficients. Our approach uses two separate GPR kernels for lung and non-lung tissues. For non-lung tissues, the co-registered atlas dataset was sorted on the basis of local normalized cross-correlation similarity to the target MR image to select the most similar image in the atlas for each voxel. For lung tissue, the lung volume was incorporated in the GPR kernel taking advantage of the correlation between lung volume and corresponding attenuation properties to predict the attenuation coefficients of the lung. In the presence of pathological tissues in the lungs, the lesions are segmented on PET images corrected for attenuation using MRI-derived three-class attenuation map followed by assignment of soft-tissue attenuation coefficient. The proposed algorithm was compared to other techniques reported in the literature including Hofmann's approach and the three-class attenuation correction technique implemented on the Philips Ingenuity TF PET/MR where CT-based attenuation correction served as reference. Fourteen patients with head and neck cancer undergoing PET/CT and PET/MR examinations were used for quantitative analysis. SUV measurements were performed on 12 normal uptake regions as well as high uptake malignant regions. Moreover, a number of similarity measures were used to evaluate the accuracy of extracted bones. The Dice similarity metric revealed that the extracted bone improved from 0.58±0.09 to 0.65±0.07 when using the SAP technique compared to Hofmann's approach. This enabled to reduce the SUV mean bias in bony structures for the SAP approach to -1.7±4.8{\%} as compared to -7.3±6.0{\%} and -27.4±10.1{\%} when using Hofmann's approach and the three-class attenuation map, respectively. Likewise, the three-class attenuation map produces a relative absolute error of 21.7±11.8{\%} in the lungs. This was reduced on average to 15.8±8.6{\%} and 8.0±3.8{\%} when using Hofmann's and SAP techniques, respectively. The SAP technique resulted in better overall PET quantification accuracy than both Hofmann's and the three-class approaches owing to the more accurate extraction of bones and better prediction of lung attenuation coefficients. Further improvement of the technique and reduction of the computational time are still required.},
author = {Arabi, Hossein and Zaidi, Habib},
doi = {10.1016/j.media.2016.02.002},
issn = {13618423},
journal = {Medical Image Analysis},
keywords = {Atlas,Attenuation correction,PET/MRI,Pseudo-CT generation,Quantification},
pages = {1--15},
title = {{Magnetic resonance imaging-guided attenuation correction in whole-body PET/MRI using a sorted atlas approach}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {31},
year = {2016}
}
@article{Asadulina2012,
abstract = {Background: Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development.Results: Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to these templates the expression patterns of cell-type specific genes. In order to evaluate the gene expression pattern registration, we analyzed the absolute deviation of cell-center positions. Both the acetylated-tubulin- and the nuclear-stain-based templates allowed near-cellular-resolution gene expression registration. Nuclear-stain-based templates often performed significantly better than acetylated-tubulin-based templates. We provide detailed guidelines and scripts for the use and further expansion of the Platynereis gene expression atlas.Conclusions: We established whole-body reference templates for the generation of gene expression atlases for Platynereis trochophore and nectochaete larvae. We anticipate that nuclear-staining-based image registration will be applicable for whole-body alignment of the embryonic and larval stages of other organisms in a similar size range. {\textcopyright} 2012 Asadulina et al.; licensee BioMed Central Ltd.},
author = {Asadulina, Albina and Panzera, Aurora and Veraszt{\'{o}}, Csaba and Liebig, Christian and J{\'{e}}kely, G{\'{a}}sp{\'{a}}r},
doi = {10.1186/2041-9139-3-27},
issn = {20419139},
journal = {EvoDevo},
number = {1},
pages = {12},
title = {{Whole-body gene expression pattern registration in Platynereis larvae}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {3},
year = {2012}
}
@article{Avants2014,
abstract = {Publicly available scientific resources help establish evaluation standards, provide a platform for teaching and improve reproducibility. Version 4 of the Insight ToolKit (ITK4) seeks to establish new standards in publicly available image registration methodology. ITK4 makes several advances in comparison to previous versions of ITK. ITK4 supports both multivariate images and objective functions; it also unifies high-dimensional (deformation field) and low-dimensional (affine) transformations with metrics that are reusable across transform types and with composite transforms that allow arbitrary series of geometric mappings to be chained together seamlessly. Metrics and optimizers take advantage of multi-core resources, when available. Furthermore, ITK4 reduces the parameter optimization burden via principled heuristics that automatically set scaling across disparate parameter types (rotations vs. translations). A related approach also constrains steps sizes for gradient-based optimizers. The result is that tuning for different metrics and/or image pairs is rarely necessary allowing the researcher to more easily focus on design/comparison of registration strategies. In total, the ITK4 contribution is intended as a structure to support reproducible research practices, will provide a more extensive foundation against which to evaluate new work in image registration and also enable application level programmers a broad suite of tools on which to build. Finally, we contextualize this work with a reference registration evaluation study with application to pediatric brain labeling. {\textcopyright} 2014 Avants, Tustison, Stauffer, Song, Wuand Gee.},
author = {Avants, Brian B. and Tustison, Nicholas J. and Stauffer, Michael and Song, Gang and Wu, Baohua and Gee, James C.},
doi = {10.3389/fninf.2014.00044},
issn = {16625196},
journal = {Frontiers in Neuroinformatics},
keywords = {Brain,Death,MRI,Open-source,Registration},
number = {APR},
pages = {13},
title = {{The Insight ToolKit image registration framework}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {8},
year = {2014}
}
@article{B?rdosi2020,
abstract = {Purpose : A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal mental and workload overhead on surgeons working without a monitor and dedicated pointing tools. Methods : Three components were developed: a registration tool (Rhinospider), a hybrid magneto-optic-tracked robotic feedback control scheme and a modified robotic end-effector. Rhinospider optimizes registration of patient and preoperative CT data by excluding user errors in fiducial localization with magnetic tracking. The hybrid controller uses an integrated microscope HD camera for robotic control with a guidance beam shining on a dual plate setup avoiding magnetic field distortions. A robotic needle insertion platform (iSYS Medizintechnik GmbH, Austria) was modified to position a laser beam with high precision in a surgical scene compatible to microscopic surgery. Results : System accuracy was evaluated quantitatively at various target positions on a phantom. The accuracy found is 1.2 mm ± 0.5 mm. Errors are primarily due to magnetic tracking. This application accuracy seems suitable for most surgical procedures in the lateral skull base. The system was evaluated quantitatively during a mastoidectomy of an anatomic head specimen and was judged useful by the surgeon. Conclusion : A hybrid robotic laser guidance system with direct visual feedback is proposed for navigated drilling and intraoperative structure localization. The system provides visual cues directly on/in the patient anatomy, reducing the standard limitations of AR visualizations like depth perception. The custom- built end-effector for the iSYS robot is transparent to using surgical microscopes and compatible with magnetic tracking. The cadaver experiment showed that guidance was accurate and that the end-effector is unobtrusive. This laser guidance has potential to aid the surgeon in finding the optimal mastoidectomy trajectory in more difficult interventions.},
author = {B{\'{a}}rdosi, Zolt{\'{a}}n and Plattner, Christian and {\"{O}}zbek, Yusuf and Hofmann, Thomas and Milosavljevic, Srdjan and Schartinger, Volker and Freysinger, Wolfgang},
doi = {10.1007/s11548-019-02066-1},
issn = {18616429},
journal = {International Journal of Computer Assisted Radiology and Surgery},
keywords = {Augmented reality,Laser guidance,Magnetic tracking,Microscope,Navigated surgery,Optical tracking,Robotic control},
number = {1},
pages = {49--57},
title = {{CIGuide: in situ augmented reality laser guidance}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {15},
year = {2020}
}
@inbook{Baglaeva2016,
address = {Paris},
author = {Baglaeva, Elena and Tsapko, Sergey and Tsapko, Irina and Ershov, Aleksey},
booktitle = {Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine},
doi = {10.2991/itsmssm-16.2016.95},
editor = {Berestneva, O and Tikhomirov, A and Trufanov, A},
isbn = {978-94-6252-196-4},
pages = {354--358},
publisher = {Atlantis Press},
series = {ACSR-Advances in Comptuer Science Research},
title = {{Modelling of Cellular Structures Obtained By X-Ray Phase Contrast Imaging}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {51},
year = {2016}
}
@article{Bailey2017,
abstract = {The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.},
author = {Bailey, Colleen and Siow, Bernard and Panagiotaki, Eleftheria and Hipwell, John H. and Mertzanidou, Thomy and Owen, Julie and Gazinska, Patrycja and Pinder, Sarah E. and Alexander, Daniel C. and Hawkes, David J.},
doi = {10.1002/nbm.3679},
issn = {10991492},
journal = {NMR in Biomedicine},
keywords = {DTI,MRI,anisotropy,breast cancer,diffusion,ex vivo,restriction},
number = {2},
pages = {13},
title = {{Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {30},
year = {2017}
}
@article{Bajcsy2015,
abstract = {Background: The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements. Methods: We define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories. Results: The survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue. Conclusions: The novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.},
author = {Bajcsy, Peter and Cardone, Antonio and Chalfoun, Joe and Halter, Michael and Juba, Derek and Kociolek, Marcin and Majurski, Michael and Peskin, Adele and Simon, Carl and Simon, Mylene and Vandecreme, Antoine and Brady, Mary},
doi = {10.1186/s12859-015-0762-2},
issn = {14712105},
journal = {BMC Bioinformatics},
keywords = {Accelerated execution of segmentation for high-thr,Cell segmentation,Cellular measurements,Segmentation evaluation,Segmented objects},
number = {1},
pages = {28},
title = {{Survey statistics of automated segmentations applied to optical imaging of mammalian cells}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {16},
year = {2015}
}
@article{Balasubramanian2019,
abstract = {Retinal image analysis relies on the effectiveness of computational techniques to discriminate various abnormalities in the eye like diabetic retinopathy, macular degeneration and glaucoma. The onset of the disease is often unnoticed in case of glaucoma, the effect of which is felt only at a later stage. Diagnosis of such degenerative diseases warrants early diagnosis and treatment. In this work, performance of statistical and textural features in retinal vessel segmentation is evaluated through classifiers like extreme learning machine, support vector machine and Random Forest. The fundus images are initially preprocessed for any noise reduction, image enhancement and contrast adjustment. The two-dimensional Gabor Wavelets and Partition Clustering is employed on the preprocessed image to extract the blood vessels. Finally, the combined hybrid features comprising statistical textural, intensity and vessel morphological features, extracted from the image, are used to detect glaucomatous abnormality through the classifiers. A crisp decision can be taken depending on the classifying rates of the classifiers. Public databases RIM-ONE and high-resolution fundus and local datasets are used for evaluation with threefold cross validation. The evaluation is based on performance metrics through accuracy, sensitivity and specificity. The evaluation of hybrid features obtained an overall accuracy of 97{\%} when tested using classifiers. The support vector machine classifier is able to achieve an accuracy of 93.33{\%} on high-resolution fundus, 93.8{\%} on RIM-ONE dataset and 95.3{\%} on local dataset. For extreme learning machine classifier, the accuracy is 95.1{\%} on high-resolution fundus, 97.8{\%} on RIM-ONE and 96.8{\%} on local dataset. An accuracy of 94.5{\%} on high-resolution fundus 92.5{\%} on RIM-ONE and 94.2{\%} on local dataset is obtained for the random forest classifier. Validation of the experiment results indicate that the hybrid features can be deployed in supervised classifiers to discriminate retinal abnormalities effectively.},
author = {Balasubramanian, Kishore and Ananthamoorthy, N. P.},
doi = {10.1177/0954411919835856},
issn = {20413033},
journal = {Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine},
keywords = {Glaucoma,blood vessel,classifier,clustering,feature selection,fundus image,thresholding},
number = {5},
pages = {506--514},
title = {{Analysis of hybrid statistical textural and intensity features to discriminate retinal abnormalities through classifiers}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {233},
year = {2019}
}
@article{Barnes2010,
abstract = {Introduction We aimed to assess the value of a second MR scan in the radiological diagnosis of dementia. Methods One hundred twenty subjects with clinical followup of at least 1 year with two scans were selected from a cognitive disorders clinic. Scans were reviewed as a single first scan (method A), two unregistered scans presented sideby- side (method B) and a registered pair (method C). Scans were presented to two neuroradiologists and a clinician together with approximate scan interval (if applicable) and age. Raters decided on a main and subtype diagnosis. Results There was no evidence that differences between methods (expressed as relative odds of a correct response) differed between reviewers (p=0.17 for degenerative condition or not, p=0.5 for main diagnosis, p=0.16 for subtype). Accordingly, results were pooled over reviewers. For distinguishing normal/non-progressors from degenerative conditions, the proportions correctly diagnosed were higher with methods B and C than with A (p=0.001, both tests). The difference between method B and C was not statistically significant (p=0.18). For main diagnosis, the proportion of correct diagnoses were highest with method C for all three reviewers; however, this was not statistically significant comparing with method A (p=0.23) or with method B (p=0.16). For subtype diagnosis, there was some evidence that method C was better than method A (p=0.01) and B (p=0.048). Conclusions Serial MRI and registration may improve visual diagnosis in dementia. {\textcopyright} Springer-Verlag 2010.},
author = {Barnes, Josephine and Mitchell, L. Anne and Kennedy, Jonathan and Bastos-Leite, Antonio J. and Barker, Suzie and Lehmann, Manja and Nordstrom, R. Chris and Frost, Chris and Smith, Joseph R. and Garde, Ellen and Rossor, Martin N. and Fox, Nick C.},
doi = {10.1007/s00234-010-0665-x},
issn = {00283940},
journal = {Neuroradiology},
keywords = {Dementia,Diagnosis,Registration,Serial MRI,Visual assessment},
number = {11},
pages = {987--995},
title = {{Does registration of serial MRI improve diagnosis of dementia?}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650210726{\&}doi=10.1007{\%}2Fs00234-010-0665-x{\&}partnerID=40{\&}md5=52c55fbcb14f73d705d6a72ebba15776},
volume = {52},
year = {2010}
}
@article{BastidaJumilla2011,
abstract = {Image processing turns out to be essential in the planning and verification of radiotherapy treatments. Before applying a radiotherapy treatment, a dosimetry planning must be performed. Usually, the planning is done by means of an X-ray volumetric analysis using computerized tomography, where the area to be radiated is marked out. During the treatment phase, it is necessary to place the patient under the particle accelerator exactly as considered in the dosimetry stage. Coarse alignment is achieved using fiduciary markers placed over the patient's skin as external references. Later, fine alignment is provided by comparing a digitally reconstructed radiography (DRR) from the planning stage and a portal image captured by the accelerator in the treatment stage. The preprocessing of DRR and portal images, as well as the minimization of the non-shared information between both kinds of images, is mandatory for the correct operation of the image registration algorithm. With this purpose, mathematical morphology and image processing techniques have been used. The present work describes a fully automatic method to calculate more accurately the necessary displacement of the couch to place the patient exactly at the planned position. The proposed method to achieve the correct positioning of the patient is based on advanced image registration techniques. Preliminary results show a perfect match with the displacement estimated by the physician. {\textcopyright} Society for Imaging Informatics in Medicine 2011.},
author = {Bastida-Jumilla, Ma Consuelo and Larrey-Ruiz, Jorge and Verd{\'{u}}-Monedero, Rafael and Morales-S{\'{a}}nchez, Juan and Sancho-G{\'{o}}mez, Jos{\'{e}} Luis},
doi = {10.1007/s10278-011-9376-z},
issn = {1618727X},
journal = {Journal of Digital Imaging},
keywords = {Biomedical image analysis,Image feature enhancement,Image registration,Radiotherapy},
number = {6},
pages = {999--1009},
title = {{DRR and portal image registration for automatic patient positioning in radiotherapy treatment}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {24},
year = {2011}
}
@article{Beare2016,
abstract = {Measuring the distribution of brain tissue types (tissue classification) in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation), which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks' gestation) acquired at 30 weeks' corrected gestational age (n = 5), coronal T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5) and axial T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5). The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR) group, consisted of T2-weighted images of preterm infants (born {\textless}30 weeks' gestation) acquired shortly after birth (n = 12), preterm infants acquired at term-equivalent age (n = 12), and healthy term-born infants (born ≥38 weeks' gestation) acquired within the first 9 days of life (n = 12). For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for the cortical gray matter for coronal images acquired at 30 weeks. This demonstrates that MANTiS' performance is competitive with existing techniques. For the WUNDeR dataset, mean Dice scores comparing MANTiS with manually edited segmentations demonstrated good agreement, where all scores were above 0.75, except for the hippocampus and amygdala. The results show that MANTiS is able to segment neonatal brain tissues well, even in images that have brain abnormalities common in preterm infants. MANTiS is available for download as an SPM toolbox from http://developmentalimagingmcri.github.io/mantis},
author = {Beare, Richard J. and Chen, Jian and Kelly, Claire E. and Alexopoulos, Dimitrios and Smyser, Christopher D. and Rogers, Cynthia E. and Loh, Wai Y. and Matthews, Lillian G. and Cheong, Jeanie L.Y. and Spittle, Alicia J. and Anderson, Peter J. and Doyle, Lex W. and Inder, Terrie E. and Seal, Marc L. and Thompson, Deanne K.},
doi = {10.3389/fninf.2016.00012},
issn = {16625196},
journal = {Frontiers in Neuroinformatics},
keywords = {Magnetic resonance imaging,Neonate,Preterm birth,Statistical parametric mapping,Tissue classification},
number = {MAR},
pages = {17},
title = {{Neonatal brain tissue classification with morphological adaptation and unified segmentation}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {10},
year = {2016}
}
@article{Becker2016,
abstract = {Purpose: With higher resolutions, medical image processing operations like segmentation take more time to calculate per step. The pyramid technique is a common approach to solving this problem. Starting with a low resolution, a stepwise refinement is applied until the original resolution is reached. Methods: Our work proposes a method for deformable model segmentation that generally utilizes the common pyramid technique with our improvement, to calculate and keep synchronized all mesh resolution levels in parallel. The models are coupled to propagate their changes. It presents coupling techniques and shows approaches for synchronization. The interaction with the models is realized using springs and volcanoes, and it is evaluated for the semantics of the operation to share them across the different levels. Results: The locking overhead has been evaluated for different synchronization techniques with meshes of individual resolutions. The partial update strategy has been found to have the least locking overhead. Conclusion: Running multiple models with individual resolutions in parallel is feasible. The synchronization approach has to be chosen carefully, so that an interactive modification of the segmentation remains possible. The proposed technique is aimed at making medical image segmentation more usable while delivering high performance.},
author = {Becker, Matthias and Nijdam, Niels and Magnenat-Thalmann, Nadia},
doi = {10.1007/s11548-015-1241-y},
issn = {18616429},
journal = {International Journal of Computer Assisted Radiology and Surgery},
keywords = {Deformable models,Mesh coupling,Multi-resolution,Synchronization},
number = {5},
pages = {695--705},
title = {{Coupling strategies for multi-resolution deformable meshes: expanding the pyramid approach beyond its one-way nature}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {11},
year = {2016}
}
@article{Beriault2012,
abstract = {Purpose: Both frame-based and frameless approaches to deep brain stimulation (DBS) require planning of insertion trajectories that mitigate hemorrhagic risk and loss of neurological function. Currently, this is done by manual inspection of multiple potential electrode trajectories on MR-imaging data. We propose and validate a method for computer-assisted DBS trajectory planning. Method: Our framework integrates multi-modal MRI analysis (T1w, SWI, TOF-MRA) to compute suitable DBS trajectories that optimize the avoidance of specific critical brain structures. A cylinder model is used to process each trajectory and to evaluate complex surgical constraints described via a combination of binary and fuzzy segmented datasets. The framework automatically aggregates the multiple constraints into a unique ranking of recommended low-risk trajectories. Candidate trajectories are represented as a few well-defined cortical entry patches of best-ranked trajectories and presented to the neurosurgeon for final trajectory selection. Results: The proposed algorithm permits a search space containing over 8,000 possible trajectories to be processed in less than 20 s. A retrospective analysis on 14 DBS cases of patients with severe Parkinson's disease reveals that our framework can improve the simultaneous optimization of many pre-formulated surgical constraints. Furthermore, all automatically computed trajectories were evaluated by two neurosurgeons, were judged suitable for surgery and, in many cases, were judged preferable or equivalent to the manually planned trajectories used during the operation. Conclusions: This work provides neurosurgeons with an intuitive and flexible decision-support system that allows objective and patient-specific optimization of DBS lead trajectories, which should improve insertion safety and reduce surgical time. {\textcopyright} 2012 CARS.},
author = {B{\'{e}}riault, Silvain and Subaie, Fahd Al and Collins, D. Louis and Sadikot, Abbas F. and Pike, G. Bruce},
doi = {10.1007/s11548-012-0768-4},
issn = {18616429},
journal = {International Journal of Computer Assisted Radiology and Surgery},
keywords = {Decision-support system,Deep brain stimulation,Image-guided neurosurgery,Parkinson's disease,Preoperative planning},
number = {5},
pages = {687--704},
title = {{A multi-modal approach to computer-assisted deep brain stimulation trajectory planning}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {7},
year = {2012}
}
@inproceedings{Bernardini,
abstract = {Molecular imaging based on Fluorescence Resonance Energy Transfer (FRET) is widely used in cellular physiology both for protein-protein interaction analysis and detecting conformational changes of single proteins, e.g. during activation of signaling cascades. However, getting reliable results from FRET measurements is still hampered by methodological problems such as spectral bleed through, chromatic aberration, focal plane shifts and false positive FRET. Particularly false positive FRET signals caused by random interaction of the fluorescent dyes can easily lead to misinterpretation of the data. This work introduces a Nipkow Disc based FRET microscopy system, that is easy to operate without expert knowledge of FRET. The system automatically accounts for all relevant sources of errors and provides various result presentations of two, three and four dimensional FRET data. Two examples are given to demonstrate the scope of application. An interaction analysis of the two subunits of the hypoxia-inducible transcription factor 1 demonstrates the use of the system as a tool for protein-protein interaction analysis. As an example for time lapse observations, the conformational change of the fluorophore labeled heat shock protein 33 in the presence of oxidant stress is shown.},
author = {Bernardini, Andr{\'{e}} and Wotzlaw, Christoph and Lipinski, Hans-Gerd and Fandrey, Joachim},
booktitle = {Optics, Photonics, and Digital Technologies for Multimedia Applications},
doi = {10.1117/12.854027},
isbn = {9780819481962},
issn = {0277786X},
pages = {772311},
title = {{An automated real-time microscopy system for analysis of fluorescence resonance energy transfer}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954408709{\&}doi=10.1117{\%}2F12.854027{\&}partnerID=40{\&}md5=62af8ffb1680932adc4db6fa28a2b4f1},
volume = {7723},
year = {2010}
}
@article{Bernus2015,
abstract = {Background: Cardiovascular magnetic resonance (CMR) can through the two methods 3D FLASH and diffusion tensor imaging (DTI) give complementary information on the local orientations of cardiomyocytes and their laminar arrays. Methods: Eight explanted rat hearts were perfused with Gd-DTPA contrast agent and fixative and imaged in a 9.4T magnet by two types of acquisition: 3D fast low angle shot (FLASH) imaging, voxels 50∈×∈50∈×∈50 $\mu$m, and 3D spin echo DTI with monopolar diffusion gradients of 3.6 ms duration at 11.5 ms separation, voxels 200∈×∈200∈×∈200 $\mu$m. The sensitivity of each approach to imaging parameters was explored. Results: The FLASH data showed laminar alignments of voxels with high signal, in keeping with the presumed predominance of contrast in the interstices between sheetlets. It was analysed, using structure-tensor (ST) analysis, to determine the most (v 1ST ), intermediate (v 2ST ) and least (v 3ST ) extended orthogonal directions of signal continuity. The DTI data was analysed to determine the most (e 1DTI ), intermediate (e 2DTI ) and least (e 3DTI ) orthogonal eigenvectors of extent of diffusion. The correspondence between the FLASH and DTI methods was measured and appraised. The most extended direction of FLASH signal (v 1ST ) agreed well with that of diffusion (e 1DTI ) throughout the left ventricle (representative discrepancy in the septum of 13.3∈±∈6.7°: median∈±∈absolute deviation) and both were in keeping with the expected local orientations of the long-axis of cardiomyocytes. However, the orientation of the least directions of FLASH signal continuity (v 3ST ) and diffusion (e 3ST ) showed greater discrepancies of up to 27.9∈±∈17.4°. Both FLASH (v 3ST ) and DTI (e 3DTI ) where compared to directly measured laminar arrays in the FLASH images. For FLASH the discrepancy between the structure-tensor calculated v 3ST and the directly measured FLASH laminar array normal was of 9∈±∈7° for the lateral wall and 7∈±∈9°for the septum (median∈±∈inter quartile range), and for DTI the discrepancy between the calculated v 3DTI and the directly measured FLASH laminar array normal was 22∈±∈14°and 61∈±∈53.4°. DTI was relatively insensitive to the number of diffusion directions and to time up to 72 hours post fixation, but was moderately affected by b-value (which was scaled by modifying diffusion gradient pulse strength with fixed gradient pulse separation). Optimal DTI parameters were b∈=∈1000 mm/s2 and 12 diffusion directions. FLASH acquisitions were relatively insensitive to the image processing parameters explored. Conclusions: We show that ST analysis of FLASH is a useful and accurate tool in the measurement of cardiac microstructure. While both FLASH and the DTI approaches appear promising for mapping of the alignments of myocytes throughout myocardium, marked discrepancies between the cross myocyte anisotropies deduced from each method call for consideration of their respective limitations.},
author = {Bernus, Olivier and Radjenovic, Aleksandra and Trew, Mark L. and Legrice, Ian J. and Sands, Gregory B. and Magee, Derek R. and Smaill, Bruce H. and Gilbert, Stephen H.},
doi = {10.1186/s12968-015-0129-x},
issn = {1532429X},
journal = {Journal of Cardiovascular Magnetic Resonance},
keywords = {Cardiovascular magnetic resonance,Diffusion tensor imaging,Myocardium,Myolaminar},
number = {1},
pages = {27},
title = {{Comparison of diffusion tensor imaging by cardiovascular magnetic resonance and gadolinium enhanced 3D image intensity approaches to investigation of structural anisotropy in explanted rat hearts}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {17},
year = {2015}
}
@inproceedings{Blackburn,
abstract = {Despite significant advances in biological imaging and analysis, major
informatics challenges remain unsolved: file formats are proprietary,
storage and analysis facilities are lacking, as are standards for
sharing image data and results. While the open FITS file format is
ubiquitous in astronomy, astronomical imaging shares many challenges
with biological imaging, including the need to share large image sets
using secure, cross-platform APIs, and the need for scalable
applications for processing and visualization. The Open Microscopy
Environment (OME) is an open-source software framework developed to
address these challenges. OME tools include: an open data model for
multidimensional imaging (OME Data Model); an open file format
(OME-TIFF) and library (Bio-Formats) enabling free access to images
(5D+) written in more than 145 formats from many imaging domains,
including FITS; and a data management server (OMERO). The Java-based
OMERO client-server platform comprises an image metadata store, an image
repository, visualization and analysis by remote access, allowing
sharing and publishing of image data. OMERO provides a means to manage
the data through a multi-platform API. OMERO's model-based architecture
has enabled its extension into a range of imaging domains, including
light and electron microscopy, high content screening, digital pathology
and recently into applications using non-image data from clinical and
genomic studies. This is made possible using the Bio-Formats library.
The current release includes a single mechanism for accessing image data
of all types, regardless of original file format, via Java, C/C++ and
Python and a variety of applications and environments (e.g. ImageJ,
Matlab and R).},
author = {Blackburn, Colin and Allan, Chris and Besson, S{\'{e}}bastien and Burel, Jean-Marie and Carroll, Mark and Ferguson, Richard K. and Flynn, Helen and Gault, David and Gillen, Kenneth and Leigh, Roger and Leo, Simone and Li, Simon and Lindner, Dominik and Linkert, Melissa and Moore, Josh and Moore, William J. and Ramalingam, Balaji and Rozbicki, Emil and Rustici, Gabriella and Tarkowska, Aleksandra and Walczysko, Petr and Williams, Eleanor and Swedlow, Jason R.},
booktitle = {Software and Cyberinfrastructure for Astronomy IV},
doi = {10.1117/12.2232291},
isbn = {9781510602052},
issn = {1996756X},
pages = {991324},
title = {{The Open Microscopy Environment: open image informatics for the biological sciences}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006380046{\&}doi=10.1117{\%}2F12.2232291{\&}partnerID=40{\&}md5=e050c03cd02d1a387a82a993b146e1d1},
volume = {9913},
year = {2016}
}
@article{Blackledge2016,
abstract = {We present pyOsiriX, a plugin built for the already popular dicom viewer OsiriX that provides users the ability to extend the functionality of OsiriX through simple Python scripts. This approach allows users to integrate the many cutting-edge scientific/image-processing libraries created for Python into a powerful DICOM visualisation package that is intuitive to use and already familiar to many clinical researchers. Using pyOsiriX we hope to bridge the apparent gap between basic imaging scientists and clinical practice in a research setting and thus accelerate the development of advanced clinical image processing. We provide arguments for the use of Python as a robust scripting language for incorporation into larger software solutions, outline the structure of pyOsiriX and how it may be used to extend the functionality of OsiriX, and we provide three case studies that exemplify its utility.For our first case study we use pyOsiriX to provide a tool for smooth histogram display of voxel values within a user-defined region of interest (ROI) in OsiriX. We used a kernel density estimation (KDE) method available in Python using the scikit-learn library, where the total number of lines of Python code required to generate this tool was 22. Our second example presents a scheme for segmentation of the skeleton from CT datasets. We have demonstrated that good segmentation can be achieved for two example CT studies by using a combination of Python libraries including scikit-learn, scikit-image, SimpleITK and matplotlib. Furthermore, this segmentation method was incorporated into an automatic analysis of quantitative PET-CT in a patient with bone metastases from primary prostate cancer. This enabled repeatable statistical evaluation of PET uptake values for each lesion, before and after treatment, providing estaimes maximum and median standardised uptake values (SUVmax and SUVmed respectively). Following treatment we observed a reduction in lesion volume, SUVmax and SUVmed for all lesions, in agreement with a reduction in concurrent measures of serum prostate-specific antigen (PSA).},
author = {Blackledge, Matthew D. and Collins, David J. and Koh, Dow Mu and Leach, Martin O.},
doi = {10.1016/j.compbiomed.2015.12.002},
issn = {18790534},
journal = {Computers in Biology and Medicine},
keywords = {Computed tomography,Dicom management,Dicom visualisation,Medical imaging,OsiriX,Python,Radiology},
pages = {203--212},
title = {{Rapid development of image analysis research tools: Bridging the gap between researcher and clinician with pyOsiriX}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {69},
year = {2016}
}
@article{BonnetGarnier2018,
abstract = {Changes to the spatial organization of specific chromatin domains such as constitutive heterochromatin have been studied extensively in somatic cells. During early embryonic development, drastic epigenetic reprogramming of both the maternal and paternal genomes, followed by chromatin remodeling at the time of embryonic genome activation (EGA), have been observed in the mouse. Very few studies have been performed in other mammalian species (human, bovine, or rabbit) and the data are far from complete. During this work, we studied the three-dimensional organization of pericentromeric regions during the preimplantation period in the rabbit using specific techniques (3D-FISH) and tools (semi-automated image analysis). We observed that the pericentromeric regions (identified with specific probes for Rsat I and Rsat II genomic sequences) changed their shapes (from pearl necklaces to clusters), their nuclear localizations (from central to peripheral), as from the 4-cell stage. This reorganization goes along with histone modification changes and reduced amount of interactions with nucleolar precursor body surface. Altogether, our results suggest that the 4-cell stage may be a crucial window for events necessary before major EGA, which occurs during the 8-cell stage in the rabbit.},
author = {Bonnet-Garnier, Am{\'{e}}lie and Ki{\^{e}}u, Ki{\^{e}}n and Aguirre-Lavin, Tiphaine and Tar, Krisztina and Flores, Pierre and Liu, Zichuan and Peynot, Nathalie and Chebrout, Martine and Dinny{\'{e}}s, Andr{\'{a}}s and Duranthon, V{\'{e}}ronique and Beaujean, Nathalie},
doi = {10.1007/s00412-018-0671-z},
issn = {14320886},
journal = {Chromosoma},
keywords = {3D-FISH,Centromeres,Embryos,Epigenetic modifications,Satellite sequences},
number = {3},
pages = {387--403},
title = {{Three-dimensional analysis of nuclear heterochromatin distribution during early development in the rabbit}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {127},
year = {2018}
}
@article{Boyd2006,
abstract = {The advent of in vivo micro-computed tomography (micro-CT) provides a novel approach to measure the temporal adaptation of bone micro-architecture within an individual. Spatial alignment in the scanner between serial scans is challenging, but three-dimensional image registration can be used to superimpose the resulting image data, thus ensuring consistent regions of interest (ROI) for analysis. There have been several approaches to image registration developed, yet little is known about their application to high resolution micro-CT data. The purpose of this study was to explore combinations of three image registration similarity measures and three image interpolators, in addition to multiresolution registration configurations, for assessment of computational efficiency and accuracy on both in vitro and in vivo micro-CT data. Accuracy measures were assessed by comparison with a gold-standard reference transform based on attached fiducial markers. It was concluded that a mutual information registration similarity measure with a linear image interpolator, applied at steps of increasing image resolution, provided the best compromise between accurate and efficient results. In vivo registration of tibial bone microstructure measured in an ovariectomized rat model provided consistent ROI thus demonstrating the usefulness of three-dimensional image registration for in vivo experimental and clinical micro-CT research. It is a technique that is poised to become commonly utilized for analysis of micro-CT data to diagnose and monitor efficacy of therapy in bone diseases. {\textcopyright} 2006 Biomedical Engineering Society.},
author = {Boyd, Steven K. and Moser, Stephan and Kuhn, Michael and Klinck, Robert J. and Krauze, Peter L. and M{\"{u}}ller, Ralph and Gasser, J{\"{u}}rg A.},
doi = {10.1007/s10439-006-9168-7},
issn = {00906964},
journal = {Annals of Biomedical Engineering},
keywords = {Image registration,Micro-computed tomography,Osteoporosis,Rat models,Tibial bone micro-structure},
number = {10},
pages = {1587--1599},
title = {{Evaluation of three-dimensional image registration methodologies for in vivo micro-computed tomography}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {34},
year = {2006}
}
@article{Breighner2019,
abstract = {Background: Femoroacetabular impingement syndrome (FAIS) is a common disorder of the hip resulting in groin pain and ultimately osteoarthritis. Radiologic assessment of FAI morphologies, which may present with overlapping radiologic features of hip dysplasia, often requires the use of computed tomography (CT) for evaluation of osseous abnormality, owing to the difficulty of direct visualization of cortical and subchondral bone with conventional magnetic resonance imaging (MRI). The use of a zero echo time (ZTE) MRI pulse sequence may obviate the need for CT by rendering bone directly from MRI. Purpose/Hypothesis: The purpose was to explore the application of ZTE MRI to the assessment of osseous FAI and dysplasia morphologies of the hip. It was hypothesized that angular measurements from ZTE images would show significant agreement with measurements obtained from CT images. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: Thirty-eight hips from 23 patients were imaged with ZTE MRI and CT. Clinically relevant angular measurements of hip morphology were made in both modalities and compared to assess agreement. Measurements included coronal and sagittal center-edge angles, femoral neck-shaft angle, acetabular version (at 1-, 2-, and 3-o'clock positions), T{\"{o}}nnis angle, alpha angle, and modified-beta angle. Interrater agreement was assessed for a subset of 10 hips by 2 raters. Intermodal agreement was assessed on the complete cohort and a single rater. Results: Interrater agreement was demonstrated in both CT and ZTE, with intraclass correlation coefficient values ranging from 0.636 to 0.990 for ZTE and 0.747 to 0.983 for CT, indicating “good” to “excellent” agreement. Intermodal agreement was also shown to be significant, with intraclass correlation coefficients ranging from 0.618 to 0.904. Conclusion: Significant agreement of angular measurements for hip morphology exists between ZTE MRI and CT imaging. ZTE MRI may be an effective method to quantitatively evaluate osseous hip morphology.},
author = {Breighner, Ryan E. and Bogner, Eric A. and Lee, Susan C. and Koff, Matthew F. and Potter, Hollis G.},
doi = {10.1177/0363546519878170},
issn = {15523365},
journal = {American Journal of Sports Medicine},
keywords = {FAI,MRI,femoroacetabular impingement,imaging},
number = {14},
pages = {3460--3468},
title = {{Evaluation of Osseous Morphology of the Hip Using Zero Echo Time Magnetic Resonance Imaging}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {47},
year = {2019}
}
@article{Brown2012,
abstract = {OBJECTIVE: The development and evaluation of a computer-aided bone scan analysis technique to quantify changes in tumor burden and assess treatment effects in prostate cancer clinical trials. METHODS: We have developed and report on a commercial fully automated computer-aided detection (CAD) system. Using this system, scan images were intensity normalized, and then lesions were identified and segmented by anatomic region-specific intensity thresholding. Detected lesions were compared against expert markings to assess the accuracy of the CAD system. The metrics Bone Scan Lesion Area, Bone Scan Lesion Intensity, and Bone Scan Lesion Count were calculated from identified lesions, and their utility in assessing treatment effects was evaluated by analyzing before and after scans from metastatic castration-resistant prostate cancer patients: 10 treated and 10 untreated. In this study, patients were treated with cabozantinib, a MET/vascular endothelial growth factor inhibitor resulting in high rates of resolution of bone scan abnormalities. RESULTS: Our automated CAD system identified bone lesion pixels with 94{\%} sensitivity, 89{\%} specificity, and 89{\%} accuracy. Significant differences in changes from baseline were found between treated and untreated groups in all assessed measurements derived by our system. The most significant measure, Bone Scan Lesion Area, showed a median (interquartile range) change from baseline at week 6 of 7.13{\%} (27.61) in the untreated group compared with -73.76{\%} (45.38) in the cabozantinib-treated group (P=0.0003). CONCLUSION: Our system accurately and objectively identified and quantified metastases in bone scans, allowing for interpatient and intrapatient comparison. It demonstrates potential as an objective measurement of treatment effects, laying the foundation for validation against other clinically relevant outcome measures. Copyright {\textcopyright} Lippincott Williams {\&} Wilkins.},
author = {Brown, Matthew S. and Chu, Gregory H. and Kim, Hyun J. and Allen-Auerbach, Martin and Poon, Cheryce and Bridges, Juliette and Vidovic, Adria and Ramakrishna, Bharath and Ho, Judy and Morris, Michael J. and Larson, Steven M. and Scher, Howard I. and Goldin, Jonathan G.},
doi = {10.1097/MNM.0b013e3283503ebf},
issn = {01433636},
journal = {Nuclear Medicine Communications},
keywords = {bone neoplasms,bone scan,computer-assisted detection,computer-assisted image processing,prostate cancer,radionuclide imaging},
number = {4},
pages = {384--394},
title = {{Computer-aided quantitative bone scan assessment of prostate cancer treatment response}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {33},
year = {2012}
}
@article{Bui2013,
abstract = {Imaging has become a prevalent tool in the diagnosis and treatment of many diseases, providing a unique in vivo, multi-scale view of anatomic and physiologic processes. With the increased use of imaging and its progressive technical advances, the role of imaging informatics is now evolving-from one of managing images, to one of integrating the full scope of clinical information needed to contextualize and link observations across phenotypic and genotypic scales. Several challenges exist for imaging informatics, including the need for methods to transform clinical imaging studies and associated data into structured information that can be organized and analyzed. We examine some of these challenges in establishing imaging-based observational databases that can support the creation of comprehensive disease models. The development of these databases and ensuing models can aid in medical decision making and knowledge discovery and ultimately, transform the use of imaging to support individually-tailored patient care.},
author = {Bui, Alex A.T. and Hsu, William and Arnold, Corey and El-Saden, Suzie and Aberle, Denise R. and Taira, Ricky K.},
doi = {10.1136/amiajnl-2012-001340},
issn = {10675027},
journal = {Journal of the American Medical Informatics Association},
number = {6},
pages = {1053--1058},
title = {{Imaging-based observational databases for clinical problem solving: The role of informatics}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {20},
year = {2013}
}
@article{Bultman2014,
abstract = {Purpose To develop and demonstrate the feasibility of a new formulation for quantitative perfusion modeling in the liver using interrupted DCE-MRI data acquired during multiple sequential breathholds. Materials and Methods A new mathematical formulation to estimate quantitative perfusion parameters using interrupted data was developed. Using this method, we investigated whether a second degree-of-freedom in the tissue residue function (TRF) improves quality-of-fit criteria when applied to a dual-input single-compartment perfusion model. We subsequently estimated hepatic perfusion parameters using DCE-MRI data from 12 healthy volunteers and 9 cirrhotic patients with a history of hepatocellular carcinoma (HCC); and examined the utility of these estimates in differentiating between healthy liver, cirrhotic liver, and HCC. Results Quality-of-fit criteria in all groups were improved using a Weibull TRF (2 degrees-of-freedom) versus an exponential TRF (1 degree-of-freedom), indicating nearer concordance of source DCE-MRI data with the Weibull model. Using the Weibull TRF, arterial fraction was greater in cirrhotic versus normal liver (39 ± 23{\%} versus 15 ± 14{\%}, P = 0.07). Mean transit time (20.6 ± 4.1 s versus 9.8 ± 3.5 s, P = 0.01) and arterial fraction (39 ± 23{\%} versus 73 ± 14{\%}, P = 0.04) were both significantly different between cirrhotic liver and HCC, while differences in total perfusion approached significance. Conclusion This work demonstrates the feasibility of estimating hepatic perfusion parameters using interrupted data acquired during sequential breathholds. {\textcopyright} 2013 Wiley Periodicals, Inc.},
author = {Bultman, Eric M. and Brodsky, Ethan K. and Horng, Debra E. and Irarrazaval, Pablo and Schelman, William R. and Block, Walter F. and Reeder, Scott B.},
doi = {10.1002/jmri.24238},
issn = {15222586},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {DCE-MRI,hepatic perfusion modeling,hepatocellular carcinoma,quantitative perfusion MRI,tumor perfusion modeling},
number = {4},
pages = {853--865},
pmid = {24395144},
title = {{Quantitative hepatic perfusion modeling using DCE-MRI with sequential breathholds}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {39},
year = {2014}
}
@article{Busch2012,
abstract = {To fully describe gene expression dynamics requires the ability to quantitatively capture expression in individual cells over time. Automated systems for acquiring and analyzing real-time images are needed to obtain unbiased data across many samples and conditions. We developed a microfluidics device, the RootArray, in which 64 Arabidopsis thaliana seedlings can be grown and their roots imaged by confocal microscopy over several days without manual intervention. To achieve high throughput, we decoupled acquisition from analysis. In the acquisition phase, we obtain images at low resolution and segment to identify regions of interest. Coordinates are communicated to the microscope to record the regions of interest at high resolution. In the analysis phase, we reconstruct three-dimensional objects from stitched high-resolution images and extract quantitative measurements from a virtual medial section of the root. We tracked hundreds of roots to capture detailed expression patterns of 12 transgenic reporter lines under different conditions. {\textcopyright} 2012 Nature America, Inc. All rights reserved.},
author = {Busch, Wolfgang and Moore, Brad T. and Martsberger, Bradley and MacE, Daniel L. and Twigg, Richard W. and Jung, Jee and Pruteanu-Malinici, Iulian and Kennedy, Scott J. and Fricke, Gregory K. and Clark, Robert L. and Ohler, Uwe and Benfey, Philip N.},
doi = {10.1038/nmeth.2185},
issn = {15487091},
journal = {Nature Methods},
number = {11},
pages = {1101--1106},
title = {{A microfluidic device and computational platform for high-throughput live imaging of gene expression}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {9},
year = {2012}
}
@article{Buzzatti2019,
abstract = {The objective of the current study was to explore the potential of dynamic computed tomography to detect kinematic changes, induced by sequential sectioning of the lateral collateral ligaments of the ankle, during full motion sequence of the talocrural joint. A custom-made device was used to induce cyclic controlled ankle inversion movement in one fresh frozen cadaver leg. A 256-slice CT scanner was used to investigate four different scenarios. Scenario 1 with all ligaments intact was first investigated followed by sequential section of the anterior talo-fibular ligament (Scenario 2), the calcaneo-fibular ligament (Scenario 3) and posterior talo-fibular ligament (Scenario 4). Off-line image processing based on semi-automatic segmentation and bone rigid registration was performed. Motion parameters such as translation, rotational angles and orientation and position of the axis of rotation were calculated. Differences between scenarios were calculated. Progressive increase of cranio-caudal displacement up to 3.9 mm and flexion up to 10° compared to Scenario 1 were reported. Progressive changes in orientation (up to 20.6°) and position (up to 4.1 mm) of the axis of rotation were also shown. Estimated effective dose of 0.005 mSv (1.9 mGy CTDIvol) was reported. This study demonstrated that kinematic changes due to the absence of ligament integrity can be detected with 4DCT with minimal radiation exposure. Identifying abnormal kinematic patterns could have future application in helping clinicians to choose patients' optimal treatment. Therefore, further studies with bigger in vitro sample sizes and consequent investigations in vivo are recommended to confirm the current findings.},
author = {Buzzatti, Luca and Keelson, Benyameen and Apperloo, Jildert and Scheerlinck, Thierry and Baeyens, Jean Pierre and {Van Gompel}, Gert and Vandemeulebroucke, Jef and de Maeseneer, Michel and de Mey, Johan and Buls, Nico and Cattrysse, Erik},
doi = {10.1038/s41598-018-38101-5},
issn = {20452322},
journal = {Scientific Reports},
number = {1},
pages = {9},
title = {{Four-dimensional CT as a valid approach to detect and quantify kinematic changes after selective ankle ligament sectioning}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {9},
year = {2019}
}
@inproceedings{Calvini,
abstract = {Atrophy and other brain changes, which are typical of aging, generate wide inter-individual variability of morphology in the medial temporal lobe (MTL), including the hippocampal formation. Starting from a sample population of 133 MR images we developed a procedure that extracts from each MR two sub images, containing the hippocampal formations plus a portion of the adjacent tissues and cavities. Then, a small number of templates is selected among the previously obtained sub images, able to describe the morphological variability present in the whole population. Finally an automatic procedure is prepared which, on the basis of the given set of templates, is able to find both hippocampal formations in any new MR image. MR images ranging from normalcy to extreme atrophy can be successfully processed. The proposed approach, besides being a preliminary step towards the unsupervised segmentation of the hippocampus, extracts from the MR image information useful for diagnostic purposes and, in particular, could give the possibility of performing morphometric studies on the medial temporal lobe in an automated way. The automated analysis of MTL atrophy in the segmented volume is readily applied to the early assessment of Alzheimer Disease (AD), leading to discriminating converters from Mild Cognitive Impairment (MCI) to AD with an average three years follow-up. This procedure can quickly and reliably provide additional information in early diagnosis of AD. {\textcopyright} 2008 IEEE.},
author = {Calvini, Piero and Chincarini, Andrea and Donadio, Stefania and Gemme, Gianluca and Squarcia, Sandro and Nobili, Flavio and Rodriguez, Guido and Bellotti, Roberto and Catanzariti, Ezio and Cerello, Piergiorgio and {De Mitri}, Ivan and Fantacci, Maria Evelina},
booktitle = {IEEE Nuclear Science Symposium Conference Record},
doi = {10.1109/NSSMIC.2008.4774245},
isbn = {9781424427154},
issn = {10957863},
pages = {4348--4354},
title = {{Automatic localization of the hippocampal region in MR images to asses early diagnosis of Alzheimer's disease in MCI patients}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-67649172535{\&}doi=10.1109{\%}2FNSSMIC.2008.4774245{\&}partnerID=40{\&}md5=0876425a595d10f8641904244780ec81},
year = {2008}
}
@article{Captur2015,
abstract = {Many of the structures and parameters that are detected, measured and reported in cardiovascular magnetic resonance (CMR) have at least some properties that are fractal, meaning complex and self-similar at different scales. To date however, there has been little use of fractal geometry in CMR; by comparison, many more applications of fractal analysis have been published in MR imaging of the brain. This review explains the fundamental principles of fractal geometry, places the fractal dimension into a meaningful context within the realms of Euclidean and topological space, and defines its role in digital image processing. It summarises the basic mathematics, highlights strengths and potential limitations of its application to biomedical imaging, shows key current examples and suggests a simple route for its successful clinical implementation by the CMR community. By simplifying some of the more abstract concepts of deterministic fractals, this review invites CMR scientists (clinicians, technologists, physicists) to experiment with fractal analysis as a means of developing the next generation of intelligent quantitative cardiac imaging tools.},
author = {Captur, Gabriella and Karperien, Audrey L. and Li, Chunming and Zemrak, Filip and Tobon-Gomez, Catalina and Gao, Xuexin and Bluemke, David A. and Elliott, Perry M. and Petersen, Steffen E. and Moon, James C.},
doi = {10.1186/s12968-015-0179-0},
issn = {1532429X},
journal = {Journal of Cardiovascular Magnetic Resonance},
keywords = {Cardiovascular magnetic resonance,Image processing,Segmentation},
number = {1},
pages = {10},
title = {{Fractal frontiers in cardiovascular magnetic resonance: Towards clinical implementation}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {17},
year = {2015}
}
@article{Caruso2018,
abstract = {Purpose: Haralick features Texture analysis is a recent oncologic imaging biomarker used to assess quantitatively the heterogeneity within a tumor. The aim of this study is to evaluate which Haralick's features are the most feasible in predicting tumor response to neoadjuvant chemoradiotherapy (CRT) in colorectal cancer. Materials and Methods: After MRI and histological assessment, eight patients were enrolled and divided into two groups based on response to neoadjuvant CRT in complete responders (CR) and non-responders (NR). Oblique Axial T2-weighted MRI sequences before CRT were analyzed by two radiologists in consensus drawing a ROI around the tumor. 14 over 192 Haralick's features were extrapolated from normalized gray-level co-occurrence matrix in four different directions. A dedicated statistical analysis was performed to evaluate distribution of the extracted Haralick's features computing mean and standard deviation. Results: Pretreatment MRI examination showed significant value (p {\textless} 0.05) of 5 over 14 computed Haralick texture. In particular, the significant features are the following: concerning energy, contrast, correlation, entropy and inverse difference moment. Conclusions: Five Haralick's features showed significant relevance in the prediction of response to therapy in colorectal cancer and might be used as additional imaging biomarker in the oncologic management of colorectal patients.},
author = {Caruso, Damiano and Zerunian, Marta and Ciolina, Maria and de Santis, Domenico and Rengo, Marco and Soomro, Mumtaz H. and Giunta, Gaetano and Conforto, Silvia and Schmid, Maurizio and Neri, Emanuele and Laghi, Andrea},
doi = {10.1007/s11547-017-0833-8},
issn = {18266983},
journal = {Radiologia Medica},
keywords = {Colorectal cancer,Haralick's texture analysis,Response to therapy,T2-weighted MRI},
number = {3},
pages = {161--167},
title = {{Haralick's

license_type: permissive

branch_name: refs/heads/master

extension: bib