text:
to about 2 mm. As a result, ultra-fast balanced SSFP provides artifact-free images even for targets with severe susceptibility variations, and native high-resolution structural and functional in vivo 1H imaging of the human lung is demonstrated at 1.5 T. Conclusion On clinical whole body MRI systems, the TR of SSFP-based Cartesian imaging can be pushed toward the 1 ms regime. As a result, ultra-fast SSFP protocols might represent a promising new powerful approach for SSFP-based imaging, not only for lung but also in a variety of clinical and scientific applications. Copyright {\textcopyright} 2013 Wiley Periodicals, Inc.},
author = {Bieri, Oliver},
doi = {10.1002/mrm.24858},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {SSFP,imaging,lung,steady state,ultra-fast},
number = {3},
pages = {657--663},
title = {{Ultra-fast steady state free precession and its application to in vivo 1H morphological and functional lung imaging at 1.5 tesla}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883229895{\&}doi=10.1002{\%}2Fmrm.24858{\&}partnerID=40{\&}md5=8542d776ecb40faea69bd7bf6e63ebf1},
volume = {70},
year = {2013}
}
@article{Ceranka2020,
abstract = {Purpose: To improve multi-atlas segmentation of the skeleton from whole-body MRI. In particular, we study the effect of employing the atlas segmentations to iteratively mask tissues outside of the region of interest to improve the atlas alignment and subsequent segmentation. Methods: An improved atlas registration scheme is proposed. Starting from a suitable initial alignment, the alignment is refined by introducing additional stages of deformable registration during which the image sampling is limited to the dilated atlas segmentation label mask. The performance of the method was demonstrated using leave-one-out cross-validation using atlases of 10 whole-body 3D-T1 images of prostate cancer patients with bone metastases and healthy male volunteers, and compared to existing state of the art. Both registration accuracy and resulting segmentation quality, using four commonly used label fusion strategies, were evaluated. Results: The proposed method showed significant improvement in registration and segmentation accuracy with respect to the state of the art for all validation criteria and label fusion strategies, resulting in a Dice coefficient of 0.887 (STEPS label fusion). The average Dice coefficient for the multi-atlas segmentation showed over 11{\%} improvement with a decrease of false positive rate from 28.3{\%} to 13.2{\%}. For this application, repeated application of the background masking did not lead to significant improvement of the segmentation result. Conclusions: A registration strategy, relying on the use of atlas segmentations as mask during image registration was proposed and evaluated for multi-atlas segmentation of whole-body MRI. The approach significantly improved registration and final segmentation accuracy and may be applicable to other structures of interest.},
author = {Ceranka, Jakub and Verga, Sabrina and Kvasnytsia, Maryna and Lecouvet, Fr{\'{e}}d{\'{e}}ric and Michoux, Nicolas and de Mey, Johan and Raeymaekers, Hubert and Metens, Thierry and Absil, Julie and Vandemeulebroucke, Jef},
doi = {10.1002/mrm.28042},
issn = {15222594},
journal = {Magnetic Resonance in Medicine},
keywords = {atlas-based segmentation,bone segmentation,image registration,whole-body MRI},
number = {5},
pages = {1851--1862},
title = {{Multi-atlas segmentation of the skeleton from whole-body MRI—Impact of iterative background masking}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {83},
year = {2020}
}
@inproceedings{Chakraborty2016,
abstract = {{\textcopyright} 2016 SPIE. Image registration techniques using free-form deformation models have shown promising results for 3D myocardial strain estimation from ultrasound. However, the use of this technique has mostly been limited to research institutes due to the high computational demand, which is primarily due to the computational load of the regularization term ensuring spatially smooth cardiac strain estimates. Indeed, this term typically requires evaluating derivatives of the transformation field numerically in each voxel of the image during every iteration of the optimization process. In this paper, we replace this time-consuming step with a closed-form solution directly associated with the transformation field resulting in a speed up factor of ∼10-60,000, for a typical 3D B-mode image of 250 3  and 500 3  voxels, depending upon the size and the parametrization of the transformation field. The performance of the numeric and the analytic solutions was contrasted by computing tracking and strain accuracy on two realistic synthetic 3D cardiac ultrasound sequences, mimicking two ischemic motion patterns. Mean and standard deviation of the displacement errors over the cardiac cycle for the numeric and analytic solutions were 0.68±0.40 mm and 0.75±0.43 mm respectively. Correlations for the radial, longitudinal and circumferential strain components at end-systole were 0.89, 0.83 and 0.95 versus 0.90, 0.88 and 0.92 for the numeric and analytic regularization respectively. The analytic solution matched the performance of the numeric solution as no statistically significant differences (p {\textgreater} 0.05) were found when expressed in terms of bias or limits-of-Agreement.},
address = {Bellingham},
author = {Chakraborty, Bidisha and Heyde, Brecht and Alessandrini, Martino and D'hooge, Jan},
booktitle = {Medical Imaging 2016: Ultrasonic Imaging and Tomography},
doi = {10.1117/12.2216781},
editor = {Duric, N and Heyde, B},
isbn = {9781510600256},
issn = {16057422},
pages = {979006},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Fast myocardial strain estimation from 3D ultrasound through elastic image registration with analytic regularization}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976497384{\&}doi=10.1117{\%}2F12.2216781{\&}partnerID=40{\&}md5=7e796a05f80c2deec426ba41b27b2284},
volume = {9790},
year = {2016}
}
@inproceedings{Chu2013,
abstract = {Whole-body bone scintigraphy (or bone scan) is a highly sensitive method for visualizing bone metastases and is the accepted standard imaging modality for detection of metastases and assessment of treatment outcomes. The development of a quantitative biomarker using computer-aided detection on bone scans for treatment response assessment may have a significant impact on the evaluation of novel oncologic drugs directed at bone metastases. One of the challenges to lesion segmentation on bone scans is the non-specificity of the radiotracer, manifesting as high activity related to non-malignant processes like degenerative joint disease, sinuses, kidneys, thyroid and bladder. In this paper, we developed an automated bone scan lesion segmentation method that implements intensity normalization, a two-threshold model, and automated detection and removal of areas consistent with non-malignant processes from the segmentation. The two-threshold model serves to account for outlier bone scans with elevated and diffuse intensity distributions. Parameters to remove degenerative joint disease were trained using a multi-start Nelder-Mead simplex optimization scheme. The segmentation reference standard was constructed manually by a panel of physicians. We compared the performance of the proposed method against a previously published method. The results of a two-fold cross validation show that the overlap ratio improved in 67.0{\%} of scans, with an average improvement of 5.1{\%} points. {\textcopyright} 2013 SPIE.},
address = {Bellingham},
author = {Chu, Gregory H. and Lo, Pechin and Kim, Hyun J. and Auerbach, Martin and Goldin, Jonathan and Henkel, Keith and Banola, Ashley and Morris, Darren and Coy, Heidi and Brown, Matthew S.},
booktitle = {Medical Imaging 2013: Computer-Aided Diagnosis},
doi = {10.1117/12.2008082},
editor = {Novak, C L and Aylward, S},
isbn = {9780819494443},
issn = {0277786X},
pages = {867007},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Preliminary results of automated removal of degenerative joint disease in bone scan lesion segmentation}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878418964{\&}doi=10.1117{\%}2F12.2008082{\&}partnerID=40{\&}md5=a9e7952d5bc2b133959d4ad734f5d4ac},
volume = {8670},
year = {2013}
}
@inproceedings{Chu2012,
abstract = {Quantification of overall tumor area on bone scans may be a potential biomarker for treatment response assessment and has, to date, not been investigated. Segmentation of bone metastases on bone scans is a fundamental step for this response marker. In this paper, we propose a fully automated computerized method for the segmentation of bone metastases on bone scans, taking into account characteristics of different anatomic regions. A scan is first segmented into anatomic regions via an atlas-based segmentation procedure, which involves non-rigidly registering a labeled atlas scan to the patient scan. Next, an intensity normalization method is applied to account for varying levels of radiotracer dosing levels and scan timing. Lastly, lesions are segmented via anatomic regionspecific intensity thresholding. Thresholds are chosen by receiver operating characteristic (ROC) curve analysis against manual contouring by board certified nuclear medicine physicians. A leave-one-out cross validation of our method on a set of 39 bone scans with metastases marked by 2 board-certified nuclear medicine physicians yielded a median sensitivity of 95.5{\%}, and specificity of 93.9{\%}. Our method was compared with a global intensity thresholding method. The results show a comparable sensitivity and significantly improved overall specificity, with a p-value of 0.0069.},
address = {Bellingham},
author = {Chu, Gregory H. and Lo, Pechin and Kim, Hyun J. and Lu, Peiyun and Ramakrishna, Bharath and Gjertson, David and Poon, Cheryce and Auerbach, Martin and Goldin, Jonathan and Brown, Matthew S.},
booktitle = {Medical Imaging 2012: Computer-Aided Diagnosis},
doi = {10.1117/12.911462},
editor = {VanGinneken, B and Novak, C L},
isbn = {9780819489647},
issn = {16057422},
pages = {83150F},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Automated segmentation of tumors on bone scans using anatomy-specific thresholding}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874884929{\&}doi=10.1117{\%}2F12.911462{\&}partnerID=40{\&}md5=892c7bf1991afd54a3da43cf68fda6d8},
volume = {8315},
year = {2012}
}
@inbook{Corradi2009,
abstract = {The XTENS (eXTensible Environment for NeuroScience) platform consists in an highly extensible environment for collaborative work that improve repeatability of experiment and provides data storage and analysis capabilities. The platform is divided in repository and application domains, branched in services with different purpose. The first domain is the central component of the platform and consists in a multimodal repository with a client-server architecture. The second one provides remote tools for image and signal visualization and analysis. The main issue for such a platform is not only to provide an extensible collaborative environment, but also to build a development platform for testing models and algorithms in neuroscience. For these reasons a Grid approach has been considered. Both computational and data Grids infrastructures can be exploited to analyze and share large datasets of distributed data. The architecture has been deployed to support surgical planning for patients affected by drug resistant epilepsy. In that scenario, a complex analysis for a fully multimodal dataset including different image modalities, EEG and video is required to localize the origin of the ictal discharge and critical brain areas. As first results, prototype versions of both repository and application domain components are presented. {\textcopyright} 2009 The authors and IOS Press. All rights reserved.},
address = {Amsterdam},
author = {Corradi, Luca and Arnulfo, Gabriele and Schenone, Andrea and Porro, Ivan and Fato, Marco},
booktitle = {Studies in Health Technology and Informatics},
doi = {10.3233/978-1-60750-027-8-127},
editor = {Solomonides, T and HofmannApitius, M and Freudigmann, M and Semler, S C and Legre, Y and Kratz, M},
isbn = {9781607500278},
issn = {18798365},
keywords = {Collaborative environment,Data integration,Epilepsy,Grid,Multimodal and multiscale analysis,Remote visualization,Surgical planning},
pages = {127--136},
publisher = {Ios Press},
series = {Studies in Health Technology and Informatics},
title = {{XTENS - An eXTensible Environment for NeuroScience}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {147},
year = {2009}
}
@article{Crombe2019,
abstract = {Background: Standard of care for patients with high-grade soft-tissue sarcoma (STS) are being redefined since neoadjuvant chemotherapy (NAC) has demonstrated a positive effect on patients' outcome. Yet response evaluation in clinical trials still relies on RECIST criteria. Purpose: To investigate the added value of a Delta-radiomics approach for early response prediction in patients with STS undergoing NAC. Study Type: Retrospective. Population: Sixty-five adult patients with newly-diagnosed, locally-advanced, histologically proven high-grade STS of trunk and extremities. All were treated by anthracycline-based NAC followed by surgery and had available MRI at baseline and after two chemotherapy cycles. Field Strength/Sequence: Pre- and postcontrast enhanced T1-weighted imaging (T1-WI), turbo spin echo T2-WI at 1.5 T. Assessment: A threshold of {\textless}10{\%} viable cells on surgical specimens defined good response (Good-HR). Two senior radiologists performed a semantic analysis of the MRI. After 3D manual segmentation of tumors at baseline and early evaluation, and standardization of voxel-sizes and intensities, absolute changes in 33 texture and shape features were calculated. Statistical Tests: Classification models based on logistic regression, support vector machine, k-nearest neighbors, and random forests were elaborated using crossvalidation (training and validation) on 50 patients ("training cohort") and was validated on 15 other patients ("test cohort"). Results: Sixteen patients were good-HR. Neither RECIST status (P = 0.112) nor semantic radiological variables were associated with response (range of P-values: 0.134–0.490) except an edema decrease (P = 0.003), although 14 shape and texture features were (range of P-values: 0.002–0.037). On the training cohort, the highest diagnostic performances were obtained with random forests built on three features: $\Delta${\_}Histogram{\_}Entropy, $\Delta${\_}Elongation, $\Delta${\_}Surrounding{\_}Edema, which provided: area under the curve the receiver operating characteristic = 0.86, accuracy = 88.1{\%}, sensitivity = 94.1{\%}, and specificity = 66.3{\%}. On the test cohort, this model provided an accuracy of 74.6{\%} but 3/5 good-HR were systematically ill-classified. Data Conclusion: A T2-based Delta-radiomics approach might improve early response assessment in STS patients with a limited number of features. Level of Evidence: 3. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2019;50:497–510.},
author = {Cromb{\'{e}}, Amandine and P{\'{e}}rier, Cynthia and Kind, Mich{\`{e}}le and {De Senneville}, Baudouin Denis and {Le Loarer}, Fran{\c{c}}ois and Italiano, Antoine and Buy, Xavier and Saut, Olivier},
doi = {10.1002/jmri.26589},
issn = {15222586},
journal = {Journal of Magnetic Resonance Imaging},
number = {2},
pages = {497--510},
title = {{T2-based MRI Delta-radiomics improve response prediction in soft-tissue sarcomas treated by neoadjuvant chemotherapy.}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {50},
year = {2019}
}
@inbook{Santos2018,
abstract = {Evolutions in image-scanning technology have led to vast improvements in the fetal assessment. Ultrasound (US) is the main technology for fetal evaluation. Magnetic resonance imaging (MRI) is generally used when US cannot provide high-quality images. This paper presents an interactive bidirectional actuated human-machine interface proposal developed by the combination of a haptic device system (force-feedback technology) and a non-invasive medical image technology.},
address = {Cham},
author = {{Roberto Lopes dos Santos}, Jorge and Werner, Heron and Raposo, Alberto and Hurtado, Jan and Arcoverde, Vinicius and Ribeiro, Gerson},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-319-91397-1_40},
editor = {Duffy, V G},
isbn = {9783319913964},
issn = {16113349},
keywords = {Fetus,Haptics,Interaction,MRI,Ultrasound},
pages = {502--512},
publisher = {Springer International Publishing Ag},
series = {Lecture Notes in Computer Science},
title = {{A Proposal for Combining Ultrasound, Magnetic Resonance Imaging and Force Feedback Technology, During the Pregnancy, to Physically Feel the Fetus}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10917 LNCS},
year = {2018}
}
@inbook{Fallavollita2010b,
address = {Bellingham},
author = {Fallavollita, P. and KarimAghaloo, Z. and Burdette, E. C. and Song, D. Y. and Abolmaesumi, P. and Fichtinger, G.},
booktitle = {Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling},
doi = {10.1117/12.844015},
editor = {Wong, K H and Miga, M I},
isbn = {9780819480262},
issn = {16057422},
pages = {762519},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Localization of brachytherapy seeds in ultrasound by registration to fluoroscopy}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {7625},
year = {2010}
}
@article{Gaddy2015,
abstract = {Background: Features of the tumor microenvironment influence the efficacy of cancer nanotherapeutics. The ability to directly radiolabel nanotherapeutics offers a valuable translational tool to obtain biodistribution and tumor deposition data, testing the hypothesis that the extent of delivery predicts therapeutic outcome. In support of a first in-human clinical trial with 64Cu-labeled HER2-targeted liposomal doxorubicin (64Cu-MM-302), a preclinical dosimetric analysis was performed. Methods: Whole-body biodistribution and pharmacokinetic data were obtained in mice that received 64Cu-MM-302 and used to estimate absorbed radiation doses in normal human organs. PET/CT imaging revealed non-uniform distribution of 64Cu signal in mouse kidneys. Kidney micro-dosimetry analysis was performed in mice and squirrel monkeys, using a physiologically based pharmacokinetic model to estimate the full dynamics of the 64Cu signal in monkeys. Results: Organ-level dosimetric analysis of mice receiving 64Cu-MM-302 indicated that the heart was the organ receiving the highest radiation absorbed dose, due to extended liposomal circulation. However, PET/CT imaging indicated that 64Cu-MM-302 administration resulted in heterogeneous exposure in the kidney, with a focus of 64Cu activity in the renal pelvis. This result was reproduced in primates. Kidney micro-dosimetry analysis illustrated that the renal pelvis was the maximum exposed tissue in mice and squirrel monkeys, due to the highly concentrated signal within the small renal pelvis surface area. Conclusions: This study was used to select a starting clinical radiation dose of 64Cu-MM-302 for PET/CT in patients with advanced HER2-positive breast cancer. Organ-level dosimetry and kidney micro-dosimetry results predicted that a radiation dose of 400 MBq of 64Cu-MM-302 should be acceptable in patients.},
author = {Gaddy, Daniel F. and Lee, Helen and Zheng, Jinzi and Jaffray, David A. and Wickham, Thomas J. and Hendriks, Bart S.},
doi = {10.1186/s13550-015-0096-0},
issn = {2191219X},
journal = {EJNMMI Research},
keywords = {Copper-64,Dosimetry,Nanotherapeutics,Positron emission tomography},
number = {1},
pages = {10},
title = {{Whole-body organ-level and kidney micro-dosimetric evaluations of 64Cu-loaded HER2/ErbB2-targeted liposomal doxorubicin (64Cu-MM-302) in rodents and primates}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928392739{\&}doi=10.1186{\%}2Fs13550-015-0096-0{\&}partnerID=40{\&}md5=9be19ccea7a7aa4683c93949d1fae115},
volume = {5},
year = {2015}
}
@inbook{Gamarra2017,
abstract = {The advance technology in microscopy and computing has allowed the development of cell image analysis. Cloud Computing offers services, software and computing infrastructure to manage cell images' big data. However the usability of these platforms is adequate to expert users only. Many software tools are oriented to expert users in image processing, likewise the use of bioinformatics require a basic knowledge in programming. In this paper we present a framework to develop a software solution with a Service-Oriented Architecture (SOA) applied to the analysis of cell images using cloud computing.},
address = {Berlin},
author = {Gamarra, Margarita and Zurek, Eduardo and Nieto, Wilson and Jimeno, Miguel and Sierra, Deibys},
booktitle = {Advances in Intelligent Systems and Computing},
doi = {10.1007/978-3-319-56535-4_71},
editor = {Rocha, A and Correia, A M and Adeli, H and Reis, L P and Costanzo, S},
isbn = {9783319565347},
issn = {21945357},
keywords = {Bioinformatic,Cloud computing,Image processing,SOA},
pages = {724--734},
publisher = {Springer-Verlag Berlin},
series = {Advances in Intelligent Systems and Computing},
title = {{A service-oriented architecture for bioinformatics: An application in cell image analysis}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {569},
year = {2017}
}
@inbook{Gillies2018,
abstract = {Prostate cancer has the second highest noncutaneous cancer incidence in men. Three-dimensional (3D) transrectal ultrasound (TRUS) fused with a magnetic resonance image (MRI) is used to guide prostate biopsy as an alternative technique to conventional 2D TRUS sextant biopsy. The TRUS-MRI fusion technique can provide intraoperative needle guidance to suspicious cancer tissues identified on MRI, increasing the targeting capabilities of a physician. Currently, 3D TRUS-MR guided biopsy suffers from image and target misalignment caused by various forms of prostate motion. Thus, we previously developed a real-time motion compensation algorithm to align 2D and 3D TRUS images with an update rate around an ultrasound system frame rate. During clinical implementation, observations of image misalignment occurred when obtaining tissue samples near the left and right boundaries of the prostate. To minimize transducer translation on the rectal wall and avoid prostate motion and deformation, we are proposing the use of a 3D model-based ring navigation procedure. This navigation keeps the transducer positioned towards the centroid of the prostate when guiding the tracked biopsy gun to targets. Prostate biopsy was performed on three patients while using real-time motion compensation in the background. Our navigation approach was compared to a conventional 2D TRUS-guided procedure using approximately 20 2D and 3D TRUS image pairs and resulted in median {\{}[{\}}first quartile, third quartile] registration errors of 2.0 {\{}[{\}}1.3,2.5] mm and 3.4 {\{}[{\}}1.5, 8.2] mm, respectively. Using our navigation approach, registration error and variability were reduced, potentially suggesting a more robust technique when performing continuous motion compensation.},
address = {Bellingham},
author = {Tessier, David and Gillies, Derek J. and Gardi, Lori and Mercado, Ashley and Fenster, Aaron},
booktitle = {Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling},
doi = {10.1117/12.2292922},
editor = {Fei, B and Webster, R J},
isbn = {9781510616417},
issn = {16057422},
pages = {52},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Ring navigation: an ultrasound-guided technique using real-time motion compensation for prostate biopsies}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10576},
year = {2018}
}
@inbook{Gillies2017a,
abstract = {{\textcopyright} 2017 SPIE. During image-guided prostate biopsy, needles are targeted at suspicious tissues to obtain specimens that are later examined histologically for cancer. Patient motion causes inaccuracies when using MR-transrectal ultrasound (TRUS) image fusion approaches used to augment the conventional biopsy procedure. Motion compensation using a single, user initiated correction can be performed to temporarily compensate for prostate motion, but a real-time continuous registration offers an improvement to clinical workflow by reducing user interaction and procedure time. An automatic motion compensation method, approaching the frame rate of a TRUS-guided system, has been developed for use during fusion-based prostate biopsy to improve image guidance. 2D and 3D TRUS images of a prostate phantom were registered using an intensitybased algorithm utilizing normalized cross-correlation and Powell's method for optimization with user initiated and continuous registration techniques. The user initiated correction performed with observed computation times of 78 ± 35 ms, 74 ± 28 ms, and 113 ± 49 ms for in-plane, out-of-plane, and roll motions, respectively, corresponding to errors of 0.5 ± 0.5 mm, 1.5 ± 1.4 mm, and 1.5 ± 1.6°. The continuous correction performed significantly faster (p  {\textless}  0.05) than the user initiated method, with observed computation times of 31 ± 4 ms, 32 ± 4 ms, and 31 ± 6 ms for in-plane, out-of-plane, and roll motions, respectively, corresponding to errors of 0.2 ± 0.2 mm, 0.6 ± 0.5 mm, and 0.8 ± 0.4°.},
address = {Bellingham},
author = {Gillies, Derek J. and Gardi, Lori and Zhao, Ren and Fenster, Aaron},
booktitle = {Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling},
doi = {10.1117/12.2255006},
editor = {Webster, R J and Fei, B},
isbn = {9781510607156},
issn = {16057422},
pages = {101351F},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Optimization of real-time rigid registration motion compensation for prostate biopsies using 2D/3D ultrasound}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10135},
year = {2017}
}
@inbook{Haak2012a,
address = {Bellingham},
author = {Haak, Alexander and van Stralen, Marijn and van Burken, Gerard and Klein, Stefan and Pluim, Josien P. W. and de Jong, Nico and van der Steen, Antonius F. W. and Bosch, Johan G.},
booktitle = {Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy},
doi = {10.1117/12.905893},
editor = {Bosch, J G and Doyley, M M},
isbn = {9780819489692},
issn = {16057422},
pages = {832007},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Comparison of spatiotemporal interpolators for 4D image reconstruction from 2D transesophageal ultrasound}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {8320},
year = {2012}
}
@inbook{Harris2018,
abstract = {{\textcopyright} 2018 SPIE. Dilatation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). Post Hemorrhagic Ventricular Dilatation (PHVD) can lead to lifelong neurological impairment caused by ischemic injury due to increased intracranial pressure, and without treatment can lead to death. Previously, we have developed and validated a 3D ultrasound (US) system to monitor the progression of ventricle volumes (VV) in IVH patients; however, many patients with severe PHVD have ventricles so large they cannot be imaged within a single 3D US image. This limits the utility of atlas based segmentation algorithms required to measure VV as parts of the ventricles are in separate 3D US images, and thus, an already challenging segmentation becomes increasingly difficult to solve. Without a more automated segmentation, the clinical utility of 3D US ventricle volumes cannot be fully realized due to the large number of images and patients required to validate the technique in a clinical trials. Here, we describe the initial results of an automated {\^{a}}stitching' algorithm used to register and combine multiple 3D US images of the ventricles of patients with PHVD. Our registration results show that we were able to register these images with an average target registration error (TRE) of 4.25±1.95 mm.},
address = {Bellingham},
author = {Harris, Andrew and Kishimoto, Jessica and Fenster, Aaron and de Ribaupierre, Sandrine and Gardi, Lori},
booktitle = {Medical Imaging 2018: Ultrasonic Imaging and Tomography},
doi = {10.1117/12.2292925},
editor = {Duric, N and Byram, B C},
isbn = {9781510616493},
issn = {16057422},
pages = {42},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Automated registration and stitching of multiple 3D ultrasound images for monitoring neonatal intraventricular hemorrhage}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10580},
year = {2018}
}
@article{Hesse2014,
abstract = {Osteonecrosis of the jaw, in association with bisphosphonates (BRONJ) used for treating osteoporosis or cancer, is a severe and most often irreversible side effect whose underlying pathophysiological mechanisms remain largely unknown. Osteocytes are involved in bone remodeling and mineralization where they orchestrate the delicate equilibrium between osteoclast and osteoblast activity and through the active process called osteocytic osteolysis. Here, we hypothesized that (i) changes of the mineralized tissue matrix play a substantial role in the pathogenesis of BRONJ, and (ii) the osteocyte lacunar morphology is altered in BRONJ. Synchrotron $\mu$CT with phase contrast is an appropriate tool for assessing both the 3D morphology of the osteocyte lacunae and the bone matrix mass density. Here, we used this technique to investigate the mass density distribution and 3D osteocyte lacunar properties at the sub-micrometer scale in human bone samples from the jaw, femur and tibia. First, we compared healthy human jaw bone to human tibia and femur in order to assess the specific differences and address potential explanations of why the jaw bone is exclusively targeted by the necrosis as a side effect of BP treatment. Second, we investigated the differences between BRONJ and control jaw bone samples to detect potential differences which could aid an improved understanding of the course of BRONJ. We found that the apparent mass density of jaw bone was significantly smaller compared to that of tibia, consistent with a higher bone turnover in the jaw bone. The variance of the lacunar volume distribution was significantly different depending on the anatomical site. The comparison between BRONJ and control jaw specimens revealed no significant increase in mineralization after BP. We found a significant decrease in osteocyte-lacunar density in the BRONJ group compared to the control jaw. Interestingly, the osteocyte-lacunar volume distribution was not altered after BP treatment. {\textcopyright} 2014 Hesse et al.},
author = {Hesse, Bernhard and Langer, Max and Varga, Peter and Pacureanu, Alexandra and Dong, Pei and Schrof, Susanne and Man̈nicke, Nils and Suhonen, Heikki and Olivier, Cecile and Maurer, Peter and Kazakia, Galateia J. and Raum, Kay and Peyrin, Francoise},
doi = {10.1371/journal.pone.0088481},
issn = {19326203},
journal = {PLoS ONE},
number = {2},
pages = {11},
title = {{Alterations of mass density and 3D osteocyte lacunar properties in bisphosphonate-related osteonecrotic human jaw bone, a synchrotron $\mu$CT study}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {9},
year = {2014}
}
@inbook{Hoehme2017,
abstract = {In this chapter, we illustrate how three-dimensional liver tissue models can be created from experimental image modalities by utilizing a well-established processing chain of experiments, microscopic imaging, image processing, image analysis and model construction. We describe how key features of liver tissue architecture are quantified and translated into model parameterizations, and show how a systematic iteration of experiments and model simulations often leads to a better understanding of biological phenomena in systems biology and systems medicine.},
address = {Totowa},
author = {Hoehme, Stefan and Friebel, Adrian and Hammad, Seddik and Drasdo, Dirk and Hengstler, Jan G.},
booktitle = {Methods in Molecular Biology},
doi = {10.1007/978-1-4939-6506-9_22},
editor = {Stock, P and Christ, B},
isbn = {978-1-4939-6506-9; 978-1-4939-6504-5},
issn = {10643745},
keywords = {2D/3D microscopy,Confocal scanning microscopy,Hepatocyte transplantation,Liver architecture,Liver tissue model,Spatiotemporal model,Systems biology,Systems medicine,TiQuant software},
pages = {319--362},
publisher = {Humana Press Inc},
series = {Methods in Molecular Biology},
title = {{Creation of three-dimensional liver tissue models from experimental images for systems medicine}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {1506},
year = {2017}
}
@inbook{Joshi2017,
address = {Bellingham},
author = {Joshi, K. D. and Marchant, T. E. and Moore, C. J.},
booktitle = {Medical Imaging 2017: Physics of Medical Imaging},
doi = {10.1117/12.2254035},
editor = {Flohr, T G and Lo, J Y and Schmidt, T G},
isbn = {9781510607095},
issn = {16057422},
pages = {101322A},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Shading correction algorithm for cone-beam CT in radiotherapy: extensive clinical validation of image quality improvement}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10132},
year = {2017}
}
@article{Kim2014a,
abstract = {Spatiotemporal regulation of cell contractility coordinates cell shape change to construct tissue architecture and ultimately directs the morphology and function of the organism. Here we show that contractility responses to spatially and temporally controlled chemical stimuli depend much more strongly on intercellular mechanical connections than on biochemical cues in both stimulated tissues and adjacent cells. We investigate how the cell contractility is triggered within an embryonic epithelial sheet by local ligand stimulation and coordinates a long-range contraction response. Our custom microfluidic control system allows spatiotemporally controlled stimulation with extracellular ATP, which results in locally distinct contractility followed by mechanical strain pattern formation. The stimulationresponse circuit exposed here provides a better understanding of how morphogenetic processes integrate responses to stimulation and how intercellular responses are transmitted across multiple cells. These findings may enable one to create a biological actuator that actively drives morphogenesis.},
author = {Kim, Yong Tae and Hazar, Melis and Vijayraghavan, Deepthi S. and Song, Jiho and Jackson, Timothy R. and Joshi, Sagar D. and Messner, William C. and Davidson, Lance A. and LeDuc, Philip R.},
doi = {10.1073/pnas.1405209111},
issn = {10916490},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
keywords = {Mechanotransduction,Microfluidics,Multicellular,Signaling},
number = {40},
pages = {14366--14371},
title = {{Mechanochemcal actuators of embryonic epithelial contractility}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047696684{\&}doi=10.1073{\%}2Fpnas.1405209111{\&}partnerID=40{\&}md5=21fb602c98b9aba0f290a278894f3d81},
volume = {111},
year = {2014}
}
@article{Neumann2017,
abstract = {Objectives This work proposes a modular, anthropomorphic MR and CT thorax phantom that enables the comparison of experimental studies for quantitative evaluation of deformable, multimodal image registration algorithms and realistic multi-nuclear MR imaging techniques. Methods A human thorax phantom was developed with insertable modules representing lung, liver, ribs and additional tracking spheres. The quality of human tissue mimicking characteristics was evaluated for 1H and 23Na MR as well as CT imaging. The position of landmarks in the lung lobes was tracked during CT image acquisition at several positions during breathing cycles. 1H MR measurements of the liver were repeated after seven months to determine long term stability. Results The modules possess HU, T1 and T2 values comparable to human tissues (lung module: −756 ± 148 HU, artificial ribs: 218 ± 56 HU (low CaCO3 concentration) and 339 ± 121  (high CaCO3 concentration), liver module: T1 = 790 ± 28 ms, T2 = 65 ± 1 ms). Motion analysis showed that the landmarks in the lung lobes follow a 3D trajectory similar to human breathing motion. The tracking spheres are well detectable in both CT and MRI. The parameters of the tracking spheres can be adjusted in the following ranges to result in a distinct signal: HU values from 150 to 900 HU, T1 relaxation time from 550 ms to 2000 ms, T2 relaxation time from 40 ms to 200 ms. Conclusion The presented anthropomorphic multimodal thorax phantom fulfills the demands of a simple, inexpensive system with interchangeable components. In future, the modular design allows for complementing the present set up with additional modules focusing on specific research targets such as perfusion studies, 23Na MR quantification experiments and an increasing level of complexity for motion studies.},
author = {Neumann, Wiebke and Lietzmann, Florian and Schad, Lothar R. and Z{\"{o}}llner, Frank G.},
doi = {10.1016/j.zemedi.2016.07.004},
issn = {18764436},
journal = {Zeitschrift fur Medizinische Physik},
keywords = {Anthropomorphic phantom,multi-nuclear MRI,multimodal imaging,quantification,thorax phantom},
number = {2},
pages = {124--131},
title = {{Design eines multimodalen (1H/23Na MR/CT) anthropomorphen Thorax-Phantoms}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {27},
year = {2017}
}
@article{Nyholm2018,
abstract = {Purpose: We describe a public dataset with MR and CT images of patients performed in the same position with both multiobserver and expert consensus delineations of relevant organs in the male pelvic region. The purpose was to provide means for training and validation of segmentation algorithms and methods to convert MR to CT like data, i.e., so called synthetic CT (sCT). Acquisition and validation methods: T1-and T2-weighted MR images as well as CT data were collected for 19 patients at three different departments. Five experts delineated nine organs for each patient based on the T2-weighted MR images. An automatic method was used to fuse the delineations. Starting from each fused delineation, a consensus delineation was agreed upon by the five experts for each organ and patient. Segmentation overlap between user delineations with respect to the consensus delineations was measured to describe the spread of the collected data. Finally, an open-source software was used to create deformation vector fields describing the relation between MR and CT images to further increase the usability of the dataset. Data format and usage notes: The dataset has been made publically available to be used for academic purposes, and can be accessed from https://zenodo.org/record/583096. Potential applications: The dataset provides a useful source for training and validation of segmentation algorithms as well as methods to convert MR to CT-like data (sCT). To give some examples: The T2-weighted MR images with their consensus delineations can directly be used as a template in an existing atlas-based segmentation engine; the expert delineations are useful to validate the performance of a segmentation algorithm as they provide a way to measure variability among users which can be compared with the result of an automatic segmentation; and the pairwise deformably registered MR and CT images can be a source for an atlas-based sCT algorithm or for validation of sCT algorithm.},
author = {Nyholm, Tufve and Svensson, Stina and Andersson, Sebastian and Jonsson, Joakim and Sohlin, Maja and Gustafsson, Christian and Kjell{\'{e}}n, Elisabeth and S{\"{o}}derstr{\"{o}}m, Karin and Albertsson, Per and Blomqvist, Lennart and Zackrisson, Bj{\"{o}}rn and Olsson, Lars E. and Gunnlaugsson, Adalsteinn},
doi = {10.1002/mp.12748},
issn = {00942405},
journal = {Medical Physics},
keywords = {CT,MRI,open dataset,organs at risk,radiotherapy},
number = {3},
pages = {1295--1300},
title = {{MR and CT data with multiobserver delineations of organs in the pelvic area-Part of the Gold Atlas project:}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {45},
year = {2018}
}
@article{Pennati2014a,
abstract = {Purpose: To introduce a method based on multivolume proton (hydrogen [1H]) magnetic resonance (MR) imaging for the regional assessment of lung ventilatory function, investigating its use in healthy volunteers and patients with obstructive lung disease and comparing the outcome with the outcome of the research standard helium 3 (3He) MR imaging.
Materials and Methods: The institutional review board approved the HIPAA-compliant protocol, and informed written consent was obtained from each subject. Twenty-six subjects, including healthy volunteers (n = 6) and patients with severe asthma (n = 11) and mild (n = 6) and severe (n = 3) emphysema, were imaged with a 1.5-T whole-body MR unit at four lung volumes (residual volume [RV], functional residual capacity [FRC], 1 L above FRC [FRC+1 L], total lung capacity [TLC]) with breath holds of 10-11 seconds, by using volumetric interpolated breath-hold examination. Each pair of volumes were registered, resulting in maps of 1H signal change between the two lung volumes. 3He MR imaging was performed at FRC+1 L by using a two-dimensional gradient-echo sequence. 1H signal change and 3He signal were measured and compared in corresponding regions of interest selected in ventral, intermediate, and dorsal areas.
Results: In all volunteers and patients combined, proton signal difference between TLC and RV correlated positively with 3He signal (correlation coefficient R2 = 0.64, P {\textless} .001). Lower (P {\textless} .001) but positive correlation results from 1H signal difference between FRC and FRC+1 L (R2 = 0.44, P {\textless} .001). In healthy volunteers, 1H signal changes show a higher median and interquartile range compared with patients with obstructive disease and significant differences between nondependent and dependent regions.
Conclusion: Findings in this study demonstrate that multivolume 1H MR imaging, without contrast material, can be used as a biomarker for regional ventilation, both in healthy volunteers and patients with obstructive lung disease.},
author = {Pennati, Francesca and Quirk, James D. and Yablonskiy, Dmitriy A. and Castro, Mario and Aliverti, Andrea and Woods, Jason C.},
doi = {10.1148/radiol.14132470},
issn = {15271315},
journal = {Radiology},
number = {2},
pages = {580--590},
title = {{Assessment of regional lung function with multivolume 1H MR imaging in health and obstructive lung Disease: Comparison with 3He MR imaging}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910050100{\&}doi=10.1148{\%}2Fradiol.14132470{\&}partnerID=40{\&}md5=75e8d2666ef74110c8fda5fcbf082a75},
volume = {273},
year = {2014}
}
@article{Pietzsch2013,
author = {Pietzsch, Tobias and Preibisch, Stephan and Toman{\v{c}}{\'{a}}k, Pavel and Saalfeld, Stephan},
doi = {10.1093/bioinformatics/bts685},
issn = {13674803},
journal = {Bioinformatics},
number = {2},
pages = {298},
title = {{Erratum: ImgLib2 - Generic image processing in Java (Bioinformatics (2012) 28:22 (3009-3011) DOI: 10.1093/bioinformatics/bts543)}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {29},
year = {2013}
}
@inbook{Rittscher2010,
abstract = {The systems-level analysis of complex biological processes requires methods that enable the quantification of a broad range of phenotypical alterations, the precise localization of signaling events, and the ability to correlate such signaling events in the context of the spatial organization of the biological specimen. The goal of this review is to illustrate that, when combined with modern imaging platforms and labeling techniques, automated image analysis methods can provide such quantitative information. The article attempts to review necessary image analysis techniques as well as applications that utilize these techniques to provide the data that will enable systems-level biology. The text includes a review of image registration and image segmentation methods, as well as algorithms that enable the analysis of cellular architecture, cell morphology, and tissue organization. Various methods that enable the analysis of dynamic events are also presented.},
address = {Palo Alto},
author = {Rittscher, Jens},
booktitle = {Annual Review of Biomedical Engineering},
doi = {10.1146/annurev-bioeng-070909-105235},
editor = {Yarmush, M L and Duncan, J S and Gray, M L},
isbn = {978-0-8243-3512-0},
issn = {1523-9829},
number = {1},
pages = {315--344},
publisher = {Annual Reviews},
series = {Annual Review of Biomedical Engineering},
title = {{Characterization of Biological Processes through Automated Image Analysis}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {12},
year = {2010}
}
@inbook{Rusu2013,
abstract = {Statistical imaging atlases allow for integration of information from multiple patient studies collected across different image scales and modalities, such as multi-parametric (MP) MRI and histology, providing population statistics regarding a specific pathology within a single canonical representation. Such atlases are particularly valuable in the identification and validation of meaningful imaging signatures for disease characterization in vivo within a population. Despite the high incidence of prostate cancer, an imaging atlas focused on different anatomic structures of the prostate, i.e. an anatomic atlas, has yet to be constructed. In this work we introduce a novel framework for MRI atlas construction that uses an iterative, anatomically constrained registration (AnCoR) scheme to enable the proper alignment of the prostate (Pr) and central gland (CG) boundaries. Our current implementation uses endorectal, 1.5T or 3T, T2-weighted MRI from 51 patients with biopsy confirmed cancer; however, the prostate atlas is seamlessly extensible to include additional MRI parameters. In our cohort, radical prostatectomy is performed following MP-MR image acquisition; thus ground truth annotations for prostate cancer are available from the histological specimens. Once mapped onto MP-MRI through elastic registration of histological slices to corresponding T2-w MRI slices, the annotations are utilized by the AnCoR framework to characterize the 3D statistical distribution of cancer per anatomic structure. Such distributions are useful for guiding biopsies toward regions of higher cancer likelihood and understanding imaging profiles for disease extent in vivo. We evaluate our approach via the Dice similarity coefficient (DSC) for different anatomic structures (delineated by expert radiologists): Pr, CG and peripheral zone (PZ). The AnCoR-based atlas had a CG DSC of 90.36{\%}, and Pr DSC of 89.37{\%}. Moreover, we evaluated the deviation of anatomic landmarks, the urethra and veromontanum, and found 3.64 mm and respectively 4.31 mm. Alternative strategies that use only the T2-w MRI or the prostate surface to drive the registration were implemented as comparative approaches. The AnCoR framework outperformed the alternative strategies by providing the lowest landmark deviations. {\textcopyright} 2013 SPIE.},
address = {Bellingham},
author = {Rusu, Mirabela and Bloch, B. Nicolas and Jaffe, Carl C. and Rofsky, Neil M. and Genega, Elizabeth M. and Feleppa, Ernest and Lenkinski, Robert E. and Madabhushi, Anant},
booktitle = {Medical Imaging 2013: Image Processing},
doi = {10.1117/12.2006941},
editor = {Ourselin, S and Haynor, D R},
isbn = {9780819494436},
issn = {0277-786X},
pages = {866913},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Statistical 3D prostate imaging atlas construction via anatomically constrained registration}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {8669},
year = {2013}
}
@article{Santini2015,
abstract = {Purpose To develop a novel sequence for simultaneous quantification of T1 and T2 relaxation times in the myocardium based on the transient phase of the balanced steady-state free precession. Methods A new prototype sequence, named "cardiac balanced-SSFP inversion recovery with interleaved sampling acquisition" (CABIRIA) was developed based on a single-shot bSSFP readout following an inversion pulse. With this method, T1 and T2 values can be calculated from the analysis of signal evolution. The scan duration for a single slice in vivo was 8 heartbeats, thus feasible in a breath-hold. The sequence was validated both in vitro by comparing it to conventional inversion recovery and multi-echo spin-echo methods and in 5 healthy volunteers by comparing it to the Modified Look-Locker Inversion Recovery (MOLLI) sequence and to a T2 quantification sequence based on multi-T2-prepared bSSFP. Results The method showed good agreement with conventional methods for both T1 and T2 measurements (concordance correlation coefficient ≥ 0.99) in vitro. In healthy volunteers the measured T1 values were 1227 ± 68 ms and T2 values 37.9 ± 2.4 ms, with similar inter- and intrasubject variability with respect to existing methods. Conclusion The proposed CABIRIA method enables simultaneous quantification of myocardial T1 and T2 values with good accuracy and precision. Magn Reson Med 74:365-371, 2015.},
author = {Santini, Francesco and Kawel-Boehm, N. and Greiser, A. and Bremerich, J. and Bieri, O.},
doi = {10.1002/mrm.25402},
issn = {15222594},
journal = {Magnetic Resonance in Medicine},
keywords = {balanced steady-state free precession,cardiac MRI,cardiac relaxometry,inversion recovery},
number = {2},
pages = {365--371},
title = {{Simultaneous T1 and T2 quantification of the myocardium using cardiac balanced-SSFP inversion recovery with interleaved sampling acquisition (CABIRIA)}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {74},
year = {2015}
}
@book{Schober2015,
abstract = {Anatomical reference brains are indispensable tools in human brain mapping, enabling the integration of multimodal data or the alignment of a series of adjacent histological brain sections into an anatomically realistic space. This study describes a robust and efficient method for an automatic 3D reconstruction of blockface images taken from postmortem brains during cutting as a prerequisite for high-quality 3D reconstruction of brain sections. The refinement technique used in this registration method is applicable for a broad range of pre-registered histological stacks.},
address = {Berlin},
author = {Schober, Martin and Schl{\"{o}}mer, Philipp and Cremer, Markus and Mohlberg, Hartmut and Huynh, Anh Minh and Schubert, Nicole and Kirlangic, Mehmet E. and Amunts, Katrin and Axer, Markus},
booktitle = {Informatik aktuell},
doi = {10.1007/978-3-662-46224-9_26},
isbn = {9783662462232},
issn = {1431472X},
pages = {143--148},
publisher = {Springer-Verlag Berlin},
series = {Bildverarbeitung Fur Die Medizin 2015: Algorithmen - Systeme - Anwendungen},
title = {{Reference volume generation for subsequent 3D reconstruction of histological sections}},
type = {Book},
url = {{\%}3CGo to},
year = {2015}
}
@inproceedings{Sibley2016,
address = {Bellingham},
author = {Sibley, Adam R. and Markiewicz, Erica and Mustafi, Devkumar and Fan, Xiaobing and Conzen, Suzanne and Karczmar, Greg and Giger, Maryellen L.},
booktitle = {Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging},
doi = {10.1117/12.2217425},
editor = {Gimi, B and Krol, A},
isbn = {9781510600232},
issn = {16057422},
pages = {97882M},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Computerized segmentation algorithm with personalized atlases of murine MRIs in a SV40 large T-antigen mouse mammary cancer model}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978919989{\&}doi=10.1117{\%}2F12.2217425{\&}partnerID=40{\&}md5=df4d24295f5fc4323b0407742579e008},
volume = {9788},
year = {2016}
}
@article{Sobottka2013,
abstract = {Object. Intraoperative optical imaging (IOI) is an experimental technique used for visualizing functional brain areas after surgical exposure of the cerebral cortex. This technique identifies areas of local changes in blood volume and oxygenation caused by stimulation of specific brain functions. The authors describe a new IOI method, including innovative data analysis, that can facilitate intraoperative functional imaging on a routine basis. To evaluate the reliability and validity of this approach, they used the new IOI method to demonstrate visualization of the median nerve area of the somatosensory cortex. Methods. In 41 patients with tumor lesions adjacent to the postcentral gyrus, lesions were surgically removed by using IOI during stimulation of the contralateral median nerve. Optical properties of the cortical tissue were measured with a sensitive camera system connected to a surgical microscope. Imaging was performed by using 9 cycles of alternating prolonged stimulation and rest periods of 30 seconds. Intraoperative optical imaging was based on blood volume changes detected by using a filter at an isosbestic wavelength ($\lambda$ = 568 nm). A spectral analysis algorithm was used to improve computation of the activity maps. Movement artifacts were compensated for by an elastic registration algorithm. For validation, intraoperative conduction of the phase reversal over the central sulcus and postoperative evaluation of the craniotomy site were used. Results. The new method and analysis enabled significant differentiation (p {\textless} 0.005) between functional and nonfunctional tissue. The identification and visualization of functionally intact somatosensory cortex was highly reliable; sensitivity was 94.4{\%} and specificity was almost 100{\%}. The surgeon was provided with a 2D high-resolution activity map within 12 minutes. No method-related side effects occurred in any of the 41 patients. Conclusions. The authors' new approach makes IOI a contact-free and label-free optical technique that can be used safely in a routine clinical setup. Intraoperative optical imaging can be used as an alternative to other methods for the identification of sensory cortex areas and offers the added benefit of a high-resolution map of functional activity. It has great potential for visualizing and monitoring additional specific functional brain areas such as the visual, motor, and speech cortex. A prospective national multicenter clinical trial is currently being planned. {\textcopyright} AANS, 2013.},
author = {Sobottka, Stephan B. and Meyer, Tobias and Kirsch, Matthias and Koch, Edmund and Steinmeier, Ralf and Morgenstern, Ute and Schackert, Gabriele},
doi = {10.3171/2013.5.JNS122155},
issn = {00223085},
journal = {Journal of Neurosurgery},
keywords = {Brain tumors,Functional brain mapping,Functional imaging,Functional neurosurgery,Image-guided surgery,Intraoperative optical imaging,Intrinsic signals,Oncology,Somatosensory cortex},
number = {4},
pages = {853--863},
title = {{Intraoperative optical imaging of intrinsic signals: A reliable method for visualizing stimulated functional brain areas during surgery}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881515898{\&}doi=10.3171{\%}2F2013.5.JNS122155{\&}partnerID=40{\&}md5=8ed4109f65f8364384e1830b43ef2107},
volume = {119},
year = {2013}
}
@inbook{Sparks2013,
abstract = {In this work, we present a novel, automated, registration method to fuse magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) images of the prostate. Our methodology consists of: (1) delineating the prostate on MRI, (2) building a probabilistic model of prostate location on TRUS, and (3) aligning the MRI prostate segmentation to the TRUS probabilistic model. TRUS-guided needle biopsy is the current gold standard for prostate cancer (CaP) diagnosis. Up to 40{\%} of CaP lesions appear isoechoic on TRUS, hence TRUS-guided biopsy cannot reliably target CaP lesions and is associated with a high false negative rate. MRI is better able to distinguish CaP from benign prostatic tissue, but requires special equipment and training. MRI-TRUS fusion, whereby MRI is acquired pre-operatively and aligned to TRUS during the biopsy procedure, allows for information from both modalities to be used to help guide the biopsy. The use of MRI and TRUS in combination to guide biopsy at least doubles the yield of positive biopsies. Previous work on MRI-TRUS fusion has involved aligning manually determined fiducials or prostate surfaces to achieve image registration. The accuracy of these methods is dependent on the reader's ability to determine fiducials or prostate surfaces with minimal error, which is a difficult and time-consuming task. Our novel, fully automated MRI-TRUS fusion method represents a significant advance over the current state-of-the-art because it does not require manual intervention after TRUS acquisition. All necessary preprocessing steps (i.e. delineation of the prostate on MRI) can be performed offline prior to the biopsy procedure. We evaluated our method on seven patient studies, with B-mode TRUS and a 1.5 T surface coil MRI. Our method has a root mean square error (RMSE) for expertly selected fiducials (consisting of the urethra, calcifications, and the centroids of CaP nodules) of 3 .39 ± 0.85 mm. {\textcopyright} 2013 SPIE.},
address = {Bellingham},
author = {Sparks, Rachel and Bloch, B. Nicholas and Feleppa, Ernest and Barratt, Dean and Madabhushi, Anant},
booktitle = {Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling},
doi = {10.1117/12.2007610},
editor = {Holmes, D R and Yaniv, Z R},
isbn = {9780819494450},
issn = {0277-786X},
pages = {86710A},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Fully automated prostate magnetic resonance imaging and transrectal ultrasound fusion via a probabilistic registration metric}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {8671},
year = {2013}
}
@inbook{Toledo2015,
address = {Bellingham},
author = {{Velasco Toledo}, Nelson and {Romero Castro}, Eduardo},
booktitle = {10th International Symposium on Medical Information Processing and Analysis},
doi = {10.1117/12.2073319},
editor = {Romero, E and Lepore, N},
isbn = {9781628413625},
issn = {16057422},
pages = {92871C},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Fast high resolution reconstruction in multi-slice and multi-view cMRI}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {9287},
year = {2015}
}
@inbook{Toledo2013,
abstract = {Acquisition of proper cardiac MR images is highly limited by continued heart motion and apnea periods. A typical acquisition results in volumes with inter-slice separations of up to 8 mm. This paper presents a super-resolution strategy that estimates a high-resolution image from a set of low-resolution image series acquired in different non- orthogonal orientations. The proposal is based on a Bayesian approach that implements a Maximum a Posteriori (MAP) estimator combined with a Wiener filter. A pre-processing stage was also included, to correct or eliminate differences in the image intensities and to transform the low-resolution images to a common spatial reference system. The MAP estimation includes an observation image model that represents the different contributions to the voxel intensities based on a 3D Gaussian function. A quantitative and qualitative assessment was performed using synthetic and real images, showing that the proposed approach produces a high-resolution image with significant improvements (about 3dB in PSNR) with respect to a simple trilinear interpolation. The Wiener filter shows little contribution to the final result, demonstrating that the MAP uniformity prior is able to filter out a large amount of the acquisition noise. {\textcopyright} 2013 SPIE.},
address = {Bellingham},
author = {{Velasco Toledo}, Nelson and Rueda, Andrea and {Santa Marta}, Cristina and Romero, Eduardo},
booktitle = {Medical Imaging 2013: Image Processing},
doi = {10.1117/12.2007074},
editor = {Ourselin, S and Haynor, D R},
isbn = {9780819494436},
issn = {16057422},
pages = {866932},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Super-resolution in cardiac MRI using a Bayesian approach}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {8669},
year = {2013}
}
@inproceedings{Tourbier2015a,
abstract = {{\textcopyright} 2015 SPIE. In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.},
address = {Bellingham},
author = {Tourbier, S{\'{e}}bastien and Hagmann, Patric and Cagneaux, Maud and Guibaud, Laurent and Gorthi, Subrahmanyam and Schaer, Marie and Thiran, Jean-Philippe and Meuli, Reto and {Bach Cuadra}, Meritxell},
booktitle = {Medical Imaging 2015: Image Processing},
doi = {10.1117/12.2081777},
editor = {Ourselin, S and Styner, M A},
isbn = {9781628415032},
issn = {16057422},
pages = {94130Y},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Automatic brain extraction in fetal MRI using multi-atlas-based segmentation}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943378886{\&}doi=10.1117{\%}2F12.2081777{\&}partnerID=40{\&}md5=1e5911cbeee0e1cf86d55e9988c697b9},
volume = {9413},
year = {2015}
}
@inbook{Tran2017,
abstract = {{\textcopyright} 2017 SPIE. Although it is well documented that abnormal levels of either intraocular (IOP) or intracranial pressure (ICP) can lead to potentially blinding conditions, such as glaucoma and papilledema, little is known about how the pressures actually affect the eye. Even less is known about potential interplay between their effects, namely how the level of one pressure might alter the effects of the other. Our goal was to measure in-vivo the pressure-induced stretch and compression of the lamina cribrosa due to acute changes of IOP and ICP. The lamina cribrosa is a structure within the optic nerve head, in the back of the eye. It is important because it is in the lamina cribrosa that the pressure-induced deformations are believed to initiate damage to neural tissues leading to blindness. An eye of a rhesus macaque monkey was imaged in-vivo with optical coherence tomography while IOP and ICP were controlled through cannulas in the anterior chamber and lateral ventricle, respectively. The image volumes were analyzed with a newly developed digital image correlation technique. The effects of both pressures were highly localized, nonlinear and non-monotonic, with strong interactions. Pressure variations from the baseline normal levels caused substantial stretch and compression of the neural tissues in the posterior pole, sometimes exceeding 20{\%}. Chronic exposure to such high levels of biomechanical insult would likely lead to neural tissue damage and loss of vision. Our results demonstrate the power of digital image correlation technique based on non-invasive imaging technologies to help understand how pressures induce biomechanical insults and lead to vision problems.},
address = {Bellingham},
author = {Tran, H. and Grimm, J. and Wang, B. and Smith, M. A. and Gogola, A. and Nelson, S. and Tyler-Kabara, E. and Schuman, J. and Wollstein, G. and Sigal, I. A.},
booktitle = {Optical Elastography and Tissue Biomechanics IV},
doi = {10.1117/12.2257360},
editor = {Larin, K V and Sampson, D D},
isbn = {9781510605756},
issn = {0277-786X},
pages = {100670B},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Mapping in-vivo optic nerve head strains caused by intraocular and intracranial pressures}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10067},
year = {2017}
}
@inbook{Vimort2018,
abstract = {{\textcopyright} 2018 SPIE. To date, there is no single sign, symptom, or test that can clearly diagnose early stages of Temporomandibular Joint Osteoarthritis (TMJ OA). However, it has been observed that changes in the bone occur in early stages of this disease, involving structural changes both in the texture and morphometry of the bone marrow and the subchondral cortical plate. In this paper we present a tool to detect and highlight subtle variations in subchondral bone structure obtained from high resolution Cone Beam Computed Tomography (hr-CBCT) in order to help with detecting early TMJ OA. The proposed tool was developed in ITK and 3DSlicer and it has been disseminated as open-source software tools. We have validated both our texture analysis and morphometry analysis biomarkers for detection of TMJ OA comparing hr-CBCT to $\mu$CT. Our initial statistical results using the multidimensional features computed with our tool indicate that it is possible to classify areas of demonstrated loss of trabecular bone in both $\mu$CT and hr-CBCT. This paper describes the first steps to alleviate the current inability of radiological changes to diagnose TMJ OA before morphological changes are too advanced by quantifying subchondral bone biomarkers. This paper indicates that texture based and morphometry based biomarkers have the potential to identify OA patients at risk for further bone destruction.},
address = {Bellingham},
author = {Prothero, Jack and McCormick, Matthew and Paniagua, Beatriz and Vimort, Jean-Baptiste and Ruellas, Antonio Carlos and Marron, J.S. and Cevidanes, Lucia and Benavides, Erika},
booktitle = {Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging},
doi = {10.1117/12.2293654},
editor = {Gimi, B and Krol, A},
isbn = {9781510616455},
issn = {0277-786X},
pages = {25},
publisher = {Spie-Int Soc Optical Engineering},
series = {Proceedings of SPIE},
title = {{Detection of bone loss via subchondral bone analysis}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {10578},
year = {2018}
}
@inbook{Zhou2014,
abstract = {A lot of image registration algorithms are proposed in recent year, among these algorithms, which one is better or faster than the other can be only validated by experiments. In this paper, ITK (Insight Segmentation and Registration Toolkit) is used for verifying different algorithms as a framework. ITK framework requires the following components: a fixed image, a moving image, a transform, a metric, an interpolator and an optimizer. Dozens of classical algorithms are tested under the same conditions and their experimental results are demonstrated with different metrics, interpolators or optimizers. By comparison of registration time and accuracy, those practical and useful algorithms are selected for developing software in image analysis. These kinds of experiments are very valuable for software engineering, they can shorten the cycle of software development and greatly reduce the development costs. {\textcopyright} (2014) Trans Tech Publications, Switzerland.},
address = {Durnten-Zurich},
author = {Zhou, Zhen Huan},
booktitle = {Applied Mechanics and Materials},
doi = {10.4028/www.scientific.net/AMM.442.515},
editor = {Yang, G},
isbn = {9783037859018},
issn = {16609336},
keywords = {Algorithms comparison,ITK,Image registration,Registration framework},
pages = {515--519},
publisher = {Trans Tech Publications Ltd},
series = {Applied Mechanics and Materials},
title = {{Comparison and assessment of different image registration algorithms based on ITK}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {442},
year = {2014}
}
@inproceedings{Kugu2013,
abstract = {Satellite imaging is being the most attractive source of information for the governmental agencies and the commercial companies in last decade. The quality of the images is very important especially for the military or the police forces to pick the valuable information from the details. Satellite images may have unwanted signals called as noise in addition to useful information for several reasons such as heat generated electrons, bad sensor, wrong ISO settings, vibration and clouds. There are several image enhancement algorithms to reduce the effects of noise over the image to see the details and gather meaningful information. Many of these algorithms accept several parameters from the user to reach the best results. In the process of denoising, there is always a competition between the noise reduction and the fine preservation. If there is a competition between the objectives then an evolutionary multi objective optimization (EMO) is needed. In this work, the parameters of the image denoising algorithms have been optimized to minimize the trade-off by using improved Strength Pareto Evolutionary Algorithm (SPEA2). SPEA2 differs from the other EMO algorithms with the fitness assignment, the density estimation and the archive truncation processes. There is no single optimal solution in a multi objective problems instead there is a set of solutions called as Pareto efficient. Four objective functions, namely Mean Square Error (MSE), Entropy, Structural SIMilarity (SSIM) and Second Derivative of the image, have been used in this work. MSE is calculated by taking the square of difference between the noise free image and the deniosed image. Entropy is a measure of randomness of the content of difference image. The lower entropy is the better. The second derivate of an image can be achieved by convolving the image with the Laplacian Mask. SSIM algorithm is based on the similarities of the structures on the noise free image and the structures of the denoised image. For the image enhancement algorithms, Insight Segmentation and Registration Toolkit (ITK) is selected. ITK is an open source project and it is being developed in C++ to provide developers with a rich set of applications for image analysis. It includes tens of image filters for the registration and segmentation purposes. In this work, Bilateral Image Filter is evaluated in the field of satellite imaging for the noise removal process. The evaluated filter receives two parameters from the user side within their predefined ranges. Here, SPEA2 algorithm takes the responsibility to optimize these parameters to reach the best noise free image results. SPEA2 algorithm was implemented in Matlab and executable files of image filter were called in Matlab environment. The results of the work were represented graphically to show the effectiveness of selected method. {\textcopyright} 2013 IEEE.},
address = {New York},
author = {Kugu, Emin},
booktitle = {RAST 2013 - Proceedings of 6th International Conference on Recent Advances in Space Technologies},
doi = {10.1109/RAST.2013.6581204},
isbn = {9781467363938},
keywords = {Image denoising,SPEA2,bilateral filter,parameter optimization},
pages = {217--223},
publisher = {Ieee},
series = {Proceedings of 6th International Conference on Recent Advances in Space Technologies},
title = {{Satellite image denoising using Bilateral Filter with SPEA2 optimized parameters}},
type = {Book},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883888988{\&}doi=10.1109{\%}2FRAST.2013.6581204{\&}partnerID=40{\&}md5=eba34fda9e6d5ba7ef3f98fd189e8ed5 {\%}3CGo to},
year = {2013}
}
@inproceedings{Ponzio2017,
abstract = {US-guided neuronavigation exploits the simplicity of use and minimal invasiveness of Ultrasound (US) imaging and the high tissue resolution and signal-to-noise ratio of Magnetic Resonance Imaging (MRI) to guide brain surgeries. More specifically, the intra-operative 3D US images are combined with pre-operative MR images to accurately localise the course of instruments in the operative field with minimal invasiveness. Multi-modal image registration of 3D US and MR images is an essential part of such system. In this paper, we present a complete software framework that enables the registration US and MR brain scans based on a multi resolution deformable transform, tackling elastic deformations (i.e. brain shifts) possibly occurring during the surgical procedure. The framework supports also simpler and faster registration techniques, based on rigid or affine transforms, and enables the interactive visualisation and rendering of the overlaid US and MRI volumes. The registration was experimentally validated on a public dataset of realistic brain phantom images, at different levels of artificially induced deformations.},
address = {Setubal},
author = {Ponzio, Francesco and Macii, Enrico and Ficarra, Elisa and {Di Cataldo}, Santa},
booktitle = {BIOIMAGING 2017 - 4th International Conference on Bioimaging, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017},
doi = {10.5220/0006239201140121},
isbn = {9789897582158},
keywords = {Image Processing,MR-US Image Integration,Multi-modal Image Registration,Neuroimaging,US-based Neuronavigation},
pages = {114--121},
publisher = {Scitepress},
series = {Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies, Vol 2: Bioimaging},
title = {{A multi-modal brain image registration framework for US-guided neuronavigation systems integrating MR and US for minimally invasive neuroimaging}},
type = {Book},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049240676{\&}partnerID=40{\&}md5=0189c956d91dec04b477ed5846ecb930},
volume = {2017-Janua},
year = {2017}
}
@inproceedings{Mandl,
abstract = {Functional electrical stimulation (FES) of longterm denervated, degenerated human skeletal muscle has proven to be an effective method for improving a number of physiological parameters. In order to derive suitable stimulation configurations (electrode position and size) for certain muscle specific training tasks, the activation pattern induced by a given configuration must be known. The probability of activation can be estimated by activating functions which depend on the distribution of the externally applied electrical field. We thus chose to create both, a finite element (FE) and a finite difference (FD) model of the field distribution to simulate and study activation patterns and to compare their efficiency and feasibility. First preliminary results show good agreement between the two modeling approaches.},
address = {La Laguna},
author = {Mandl, Thomas and Martinek, Johannes and Mayr, Winfried and Rattay, Frank and Reichel, Martin and Moser, Ewald},
booktitle = {21st European Modeling and Simulation Symposium, EMSS 2009},
isbn = {978-84-692-5415-8},
keywords = {Finite difference method,Finite element method,Functional electrical stimulation,Patient specific model},
pages = {209--+},
publisher = {Univ De La Laguna},
series = {Emss 2009: 21st European Modeling and Simulation Symposium, Vol Ii},
title = {{Towards a numerical 3D model of functional electrical stimulation of denervated, degenerated human skeletal muscle}},
type = {Book},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874185461{\&}partnerID=40{\&}md5=a9627e50e42db43cbfa2f5ca618bdad4 {\%}3CGo to},
year = {2009}
}
@inproceedings{Medina2017,
abstract = {Cardiovascular diseases are the main cause of death in the World. This fact has motivated different actions for prevention, diagnosis and monitoring of cardiovascular diseases. In this work, the accuracy of a connected confidence left ventricle segmentation method is performed. This task is accomplished using a software platform for left ventricle segmentation of 3-D cardiac Multi-Slice Computerized Tomography (MSCT) images that is also described. The software platform has as a goal performing research about efficient methods for cardiac image segmentation and quantification. The accuracy assessment of the segmentation method is performed by comparing the estimated segmentation with respect to segmentations manually traced by cardiologists. Results show that the segmentation method provides Dice Similarity coefficients higher than 0.90 with low computational cost. The obtained segmentation is able to include within the left ventricular lumen the papillary trabeculae muscles, enabling further accurate estimation of the left ventricular mass.},
address = {New York},
author = {Medina, Ruben and Bautista, Sebastian and Morocho, Villie},
booktitle = {2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017},
doi = {10.1109/ETCM.2017.8247499},
isbn = {9781538638941},
keywords = {Connected confidence,Left ventricle segmentation,Multi-slice computerized tomography,Software platform},
pages = {1--6},
publisher = {Ieee},
series = {2017 Ieee Second Ecuador Technical Chapters Meeting},
title = {{Accuracy of connected confidence left ventricle segmentation in 3-D multi-slice computerized tomography images}},
type = {Book},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045738426{\&}doi=10.1109{\%}2FETCM.2017.8247499{\&}partnerID=40{\&}md5=31a12ff7f15e6264e843b9c8cc503a7c},
volume = {2017-Janua},
year = {2018}
}
@inproceedings{Pastorelli2014,
abstract = {The paper investigates the beneficial contribution of visual feedback in the development of an algorithm for the automatized analysis of fibre orientations in short fibre reinforced composites. Of special interest was steel fibre reinforced concrete (SFRC), a multi-disciplinary research area involving material sciences, physics and civil engineering. More in detail, this paper explains how scientific visualization techniques, employed on a Virtual Reality environment, contribute to the understanding of the SFRC properties, both for research and educational aims. Furthermore, the analysis algorithm to obtain fibre orientation distributions from noisy tomography scans is presented.},
address = {New York},
author = {Pastorelli, Emiliano and Herrmann, Heiko},
booktitle = {Proceedings of the Biennial Baltic Electronics Conference, BEC},
doi = {10.1109/BEC.2014.7320591},
isbn = {9781467395397},
issn = {17363705},
pages = {201--204},
publisher = {Ieee},
series = {2014 Proceedings of the 14th Biennial Baltic Electronics Conference},
title = {{Virtual Reality visualization for short fibre orientation analysis}},
type = {Book},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971310302{\&}doi=10.1109{\%}2FBEC.2014.7320591{\&}partnerID=40{\&}md5=3476efbc0430ba44724fcc8006637b70 {\%}3CGo to},
volume = {2015-Novem},
year = {2014}
}
@inproceedings{Haaka,
abstract = {For interventional monitoring, we aim at 4D ultrasound reconstructions of structures in the beating heart from 2D transesophageal echo images by fast scan plane rotation, unsynchronized to the heart rate. For such sparsely and irregularly sampled 2D images, a special spatiotemporal interpolation approach is desired. We have previously shown the potential of spatiotemporal interpolation by normalized convolution (NC). In this work we optimized NC for our application and compared it to nearest neighbor interpolation (NN) and to temporal binning followed by linear spatial interpolation (LTB). The test datasets consisted of 600, 1350, and 1800 2D images and were derived by slicing a 4D echocardiography data sets at random rotation angle ($\theta$, range: 0-180°) and random normalized cardiac phase ($\tau$, range: 0-1). A Gaussian kernel was used for NC and optimal kernel sizes ($\sigma$ $\tau$ and $\sigma$ $\theta$) were found by performing an exhaustive search. The RMS gray value error (RMSE) of the reconstructed images was computed for all interpolation methods. The estimated optimal kernels were $\sigma$ $\theta$=3.24°/ $\sigma$ $\tau$=0.048, $\sigma$ $\theta$=2.34°/$\sigma$ $\tau$=0.026, and $\sigma$ $\theta$=1.89°/$\sigma$ $\tau$=0.023 for 600, 1350, and 1800 input images, respectively. The minimum RMSE for NC was 13.8, 10.4, and 9.4 for 600, 1350, and 1800 input images, respectively. The NN/LTB reconstruction had an RMSE of 17.8/16.4, 13.9/15.1, and 12.0/14.7 for 600, 1350, and 1800 2D input images, respectively. We showed that NC outperforms NN and LTB. For a small number of input images the advantage of NC is more pronounced. {\textcopyright} 2011 IEEE.},
address = {New York},
author = {Haak, Alexander and {Van Stralen}, Marijn and {Van Burken}, Gerard and Klein, Stefan and Pluim, Josien P.W. and {De Jong}, Nico and {Van Der Steen}, Antonius F.W. and Bosch, Johannes G.},
booktitle = {IEEE International Ultrasonics Symposium, IUS},
doi = {10.1109/ULTSYM.2011.0038},
isbn = {9781457712531},
issn = {19485719},
pages = {152--155},
publisher = {Ieee},
series = {IEEE International Ultrasonics Symposium},
title = {{Spatiotemporal interpolation by normalized convolution for 4D transesophageal echocardiography}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869068068{\&}doi=10.1109{\%}2FULTSYM.2011.0038{\&}partnerID=40{\&}md5=e5a5718535ae51415891100024bf51a5 {\%}3CGo to},
year = {2011}
}
@incollection{Zhang2014,
abstract = {Subject-specific models of the musculoskeletal system are capable of accurately estimating function and loads and show promise for clinical use. However, creating subject-specific models is time-consuming and requires high levels of expertise. To address these issues, we have developed the open source Musculoskeletal Atlas Project (MAP) Client software. The MAP Client provides a user-friendly interface for creating musculoskeletal modelling workflows using community-created plug-ins. In this paper, we discuss the design of the MAP Client, its plug-in architecture and its integration with the Physiome Model Repository. We demonstrate the use of MAP Client with a subject-specific femur modeling workflow using a set of modular open source plug-ins for image segmentation, landmark prediction, model registration and customisation. Our long-term goal is to foster a community of MAP users and plug-in developers to accelerate the clinical use of computational models.},
address = {Cham},
author = {Zhang, Ju and Sorby, Hugh and Clement, John and Thomas, C. David L. and Hunter, Peter and Nielsen, Poul and Lloyd, David and Taylor, Mark and Besier, Thor},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-319-12057-7_21},
editor = {Bello, F and Cotin, S},
isbn = {9783319120560},
issn = {16113349},
keywords = {Biomechanical modelling,Musculoskeletal atlas project,Musculoskeletal modelling,Open source software,Personalised simulation,Pipelines,workflows},
pages = {182--192},
publisher = {Springer International Publishing Ag},
series = {Lecture Notes in Computer Science},
title = {{The MAP client: User-friendly musculoskeletal modelling workflows}},
type = {Serial},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911390478{\&}partnerID=40{\&}md5=d52525096590e132a0f2bdfbee3e3a8e},
volume = {8789},
year = {2014}
}
@inproceedings{Andrade2018,
abstract = {The large variety of medical image modalities (e.g. Computed Tomography, Magnetic Resonance Imaging, and Positron Emission Tomography) acquired from the same body region of a patient together with recent advances in computer architectures with faster and larger CPUs and GPUs allows a new, exciting, and unexplored world for image registration area. A precise and accurate registration of images makes possible understanding the etiology of diseases, improving surgery planning and execution, detecting otherwise unnoticed health problem signals, and mapping functionalities of the brain. The goal of this paper is to present a review of the state-of-the-art in medical image registration starting from the preprocessing steps, covering the most popular methodologies of the literature and finish with the more recent advances and perspectives from the application of Deep Learning architectures.},
address = {New York},
author = {Andrade, Natan and Faria, Fabio Augusto and Cappabianco, F{\'{a}}bio Augusto Menocci},
booktitle = {Proceedings - 31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018},
doi = {10.1109/SIBGRAPI.2018.00066},
isbn = {9781538692646},
keywords = {Deep Learning,Image Registration,Medical Imaging},
pages = {463--470},
publisher = {Ieee},
series = {SIBGRAPI - Brazilian Symposium on Computer Graphics and Image Processing},
title = {{A Practical Review on Medical Image Registration: From Rigid to Deep Learning Based Approaches}},
type = {Book Section},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062231809{\&}doi=10.1109{\%}2FSIBGRAPI.2018.00066{\&}partnerID=40{\&}md5=14da8e5ef491a8566fbbd2a58e32c72b},
year = {2019}
}
@inproceedings{Meesters,
abstract = {Intracranial depth electrodes are commonly used to identify the regions of the brain that are responsible for epileptic seizures. Knowledge of the exact location of the electrodes is important as to properly interpret the EEG in relation to the anatomy. In order to provide fast and accurate identification of these electrodes, a procedure has been developed for automatic detection and localization in computed tomography data. Results indicate that in the vast majority of cases the depth electrodes can be automatically found. The localization of the electrodes versus the anatomy showed an acceptably small error when compared to manual positioning. Furthermore, interactive visualization software is developed to show the detected electrodes together with pre-operative MRI images, which enables the physician to confirm that the electrode is placed at the expected anatomical location.},
address = {New York},
author = {Meesters, Stephan and Ossenblok, Pauly and Colon, Albert and Schijns, Olaf and Florack, Luc and Boon, Paul and Wagner, Louis and Fuster, Andrea},
booktitle = {Proceedings - International Symposium on Biomedical Imaging},
doi = {10.1109/ISBI.2015.7164034},
isbn = {9781479923748},
issn = {19458452},
keywords = {Computed tomography (CT),Computer-aided detection and diagnosis (CAD),Visualization},
pages = {976--979},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Automated identification of intracranial depth electrodes in computed tomography data}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944328676{\&}doi=10.1109{\%}2FISBI.2015.7164034{\&}partnerID=40{\&}md5=3989bdde301290c2ae9d67f2142f6235 {\%}3CGo to},
volume = {2015-July},
year = {2015}
}
@inproceedings{AlDhamari,
abstract = {Creating patient-specific simulation models helps to make customised implant or treatment plans. To create such models, exact locations of the Origin and Insertion Points of the Ligaments (OIPL) are required. Locating these OIPL is usually done manually through a time-consuming procedure.A fast method to detect these OIPL automatically using spine atlas-based segmentation is proposed in this paper. The average detection rate is 96.16{\%} with a standard deviation of 3.45. The required time to detect these points is approximately 5 seconds. The proposed method can be generalised to detect any other important points or features related to a specific vertebra.The method is implemented as an open-source plugin for 3D Slicer. The method and the datasets can be download for free from a public server.},
address = {New York},
author = {Al-Dhamari, Ibraheem and Bauer, Sabine and Keller, Eva and Paulus, Dietrich},
booktitle = {Proceedings - International Symposium on Biomedical Imaging},
doi = {10.1109/ISBI.2019.8759223},
isbn = {9781538636411},
issn = {19458452},
keywords = {Acir,Asgd,Atlas-segmentation,Detection,Origin and insertion points,Registration,Spine},
pages = {48--51},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Automatic detection of cervical spine ligaments origin and insertion points}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073909464{\&}doi=10.1109{\%}2FISBI.2019.8759223{\&}partnerID=40{\&}md5=1c62e6194c979866476e3863b6d3f513 {\%}3CGo to},
volume = {2019-April},
year = {2019}
}
@inproceedings{Suter2018,
abstract = {The cortical thickness and curvature of the human brain have proven to be valuable markers to detect and monitor neurodegenerative diseases [1]. Since the computational burden of currently available tools for brain morphometry is very high, this analysis often is only used for retrospective studies and not routinely in the clinics. A first attempt at a clinical use of cortical morphology is reported in [2]. We present an experiment for fast morphometry estimations using Random Forest (RF) regression [3] directly from MR imaging data. An uncertainty-aware voxel-wise, parcellation-wise, and multioutput model was built to estimate the thickness and mean curvature of the human cerebral cortex in 15 minutes instead of many hours for mesh-based tools. Preliminary results on a healthy controls database with 315 subjects show a substantial bias for the voxel-wise prediction, but high scan-rescan robustness, the proposed multi-output-parcellation prediction demonstrates the feasibility of the approach.},
address = {New York},
author = {Suter, Yannick and Rummel, Christian and Wiest, Roland and Reyes, Mauricio},
booktitle = {Proceedings - International Symposium on Biomedical Imaging},
doi = {10.1109/ISBI.2018.8363752},
isbn = {9781538636367},
issn = {19458452},
keywords = {Cortical curvature,Cortical thickness,Human brain morphometry,Machine learning,Random forest regression},
pages = {1052--1055},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Fast and uncertainty-aware cerebral cortex morphometry estimation using random forest regression}},
type = {Book Section},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048099086{\&}doi=10.1109{\%}2FISBI.2018.8363752{\&}partnerID=40{\&}md5=e22ed68e255aa6c6af3b32100df7276a},
volume = {2018-April},
year = {2018}
}
@inproceedings{Ali2007,
abstract = {Segmentation of transparent cells in brightfield microscopy images could facilitate the quantitative analysis of corresponding fluorescence images. However, this presents a challenge due to irregular morphology and weak intensity variation, particularly in ultra-thin regions. A boundary detection technique is applied to a series of variable focus images whereby a level set contour is initialised on a defocused image with improved intensity contrast, and subsequently evolved towards the correct boundary using images of improving focus. Local phase coherence is used to identify features within the images, driving contour evolution particularly in near-focus images which lack intensity contrast. Preliminary results demonstrate the effectiveness of this approach in segmenting the main cell body regions. {\textcopyright} 2007 IEEE.},
address = {New York},
author = {Ali, Rehan and Gooding, Mark and Christlieb, Martin and Brady, Michael},
booktitle = {2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings},
doi = {10.1109/ISBI.2007.356787},
isbn = {1424406722},
keywords = {Biomedical image processing,Image segmentation,Microscopy},
pages = {57--60},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Phase-based segmentation of cells from brightfield microscopy}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-36348985016{\&}doi=10.1109{\%}2FISBI.2007.356787{\&}partnerID=40{\&}md5=dd565221c35ae17147c212afbaded4f7 {\%}3CGo to},
year = {2007}
}
@inproceedings{Rezaei2013,
abstract = {To date, attenuation correction of gated PET emission data remains a challenge. Joint activity and attenuation estimation methods may contribute to solving this challenge. In this work, we demonstrate a framework in which the gated PET activity and attenuation images are jointly reconstructed and then registered to a reference frame by a joint registration approach. The method is studied and compared to common approaches by means of 2D and 3D simulations. {\textcopyright} 2013 IEEE.},
address = {New York},
author = {Rezaei, Ahmadreza and Nuyts, Johan},
booktitle = {IEEE Nuclear Science Symposium Conference Record},
doi = {10.1109/NSSMIC.2013.6829031},
isbn = {9781479905348},
issn = {10957863},
publisher = {Ieee},
series = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
title = {{Joint registration of attenuation and activity images in gated TOF-PET}},
type = {Book Section},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904204340{\&}doi=10.1109{\%}2FNSSMIC.2013.6829031{\&}partnerID=40{\&}md5=9a3c352e39a5cde2bb765fec1156cfb1},
year = {2013}
}
@inproceedings{Adluru2006,
abstract = {Segmentation of the myocardium in dynamic contrast enhanced MR short axis images is an important step towards the estimation of semi-quantitative or quantitative parameters to determine the perfusion to the tissue regions. The perfusion indices of the tissue are obtained by dividing the tissue into regions of interest and estimating perfusion to each region. A fast automatic segmentation method based on level sets has been developed that makes use of the spatial and temporal information available in the dynamic images. The algorithm is validated on cardiac data qualitatively and quantitatively by comparing against regional flow indices from manually segmented tissue regions. {\textcopyright} 2006 IEEE.},
address = {New York},
author = {Adluru, Ganesh and Dibella, Edward V.R. and Whitaker, Ross T.},
booktitle = {2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings},
doi = {10.1109/isbi.2006.1624870},
isbn = {0780395778},
pages = {133--136},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Automatic segmentation of cardiac short axis slices in perfusion MRI}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33750957116{\&}partnerID=40{\&}md5=94b184992f39bcb89fce66f4291f1585 {\%}3CGo to},
volume = {2006},
year = {2006}
}
@inproceedings{Stevenson2011,
abstract = {Studying the surface of an internal organ such as the placenta using three-dimensional ultrasound (3D US) is difficult. Image data from the surrounding tissue makes accurate identification of the interface technically challenging. The placental/maternal interface (basal plate) is thought to be the location of significant vascular pathology causing major maternal and fetal morbidity. We propose a new method for identifying this interface which combined with parameterisation (flattening) offers a novel way to study the vasculature of the developing placenta. {\textcopyright} 2011 IEEE.},
address = {New York},
author = {Stevenson, Gordon N. and Collins, Sally L. and Impey, Lawrence and Noble, J. Alison},
booktitle = {Proceedings - International Symposium on Biomedical Imaging},
doi = {10.1109/ISBI.2011.5872547},
isbn = {9781424441280},
issn = {19457928},
keywords = {Doppler measurements,Ultrasonography,anatomical structure,biomedical image processing,pregnancy},
pages = {891--894},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Surface parameterisation of the utero/placental interface using 3D power doppler ultrasound}},
type = {Book Section},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-80055033565{\&}doi=10.1109{\%}2FISBI.2011.5872547{\&}partnerID=40{\&}md5=906b8369dc14ae8e1bb4597aa31b1ec7},
year = {2011}
}
@incollection{Tourbier2014,
abstract = {Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)-based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n 2) and O(1/√$\epsilon$), while existing techniques are in O(1/n) and O(1/$\epsilon$). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy. {\textcopyright} 2014 Springer International Publishing.},
address = {Berlin},
author = {Tourbier, S{\'{e}}bastien and Bresson, Xavier and Hagmann, Patric and Thiran, Jean Philippe and Meuli, Reto and Cuadra, Meritxell Bach},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-319-10470-6_32},
editor = {Golland, P and Hata, N and Barillot, C and Hornegger, J and Howe, R},
isbn = {9783319104690},
issn = {16113349},
number = {PART 2},
pages = {252--259},
publisher = {Springer-Verlag Berlin},
series = {Lecture Notes in Computer Science},
title = {{Efficient total variation algorithm for fetal brain MRI reconstruction}},
type = {Serial},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906979454{\&}doi=10.1007{\%}2F978-3-319-10470-6{\_}32{\&}partnerID=40{\&}md5=d90bc6bfffc46271b10c0f02d0ea2f2a {\%}3CGo to},
volume = {8674 LNCS},
year = {2014}
}
@incollection{Seidel2013a,
abstract = {The segmentation of three-dimensional microscopic images of cardiac tissues provides important parameters for characterizing cardiac diseases and modeling of tissue function. Segmenting these images is, however, challenging. Currently only time-consuming manual approaches have been developed for this purpose. Here, we introduce an efficient approach for the semi-automatic segmentation (SAS) of cardiomyocytes and the extracellular space in image stacks obtained from confocal microscopy. The approach is based on a morphological watershed algorithm and iterative creation of watershed seed points on a distance map. Results of SAS were consistent with results from manual segmentation (Dice similarity coefficient: 90.8±2.6{\%}). Cell volume was 4.6±6.5{\%} higher in SAS cells, which mainly resulted from cell branches and membrane protrusions neglected by manual segmentation. We suggest that the novel approach constitutes an important tool for characterizing normal and diseased cardiac tissues. Furthermore, the approach is capable of providing crucial parameters for modeling of tissue structure and function. {\textcopyright} 2013 Springer-Verlag.},
address = {Berlin},
author = {Seidel, Thomas and Draebing, Thomas and Seemann, Gunnar and Sachse, Frank B.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-38899-6_36},
editor = {Ourselin, S and Rueckert, D and Smith, N},
isbn = {9783642388989},
issn = {03029743},
keywords = {algorithm,cardiac tissue,confocal microscopy,segmentation,three-dimensional},
pages = {300--307},
publisher = {Springer-Verlag Berlin},
series = {Lecture Notes in Computer Science},
title = {{A semi-automatic approach for segmentation of three-dimensional microscopic image stacks of cardiac tissue}},
type = {Serial},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879835400{\&}doi=10.1007{\%}2F978-3-642-38899-6{\_}36{\&}partnerID=40{\&}md5=f7e591d9366417855cbf78f95bd7e1d2 {\%}3CGo to},
volume = {7945 LNCS},
year = {2013}
}
@inproceedings{Haak2012,
abstract = {A transesophageal echocardiography (TEE) micro-probe is suitable for monitoring long minimally invasive interventions in the heart, because it is well tolerated by patients. To visualize complex 3D structures of the beating heart, a 4D-image reconstruction derived from irregularly and sparsely sampled 2D images is needed. We previously showed that normalized convolution (NC) with optimized kernels performs better than nearest-neighbor or linear interpolation. In order to use NC for image reconstructions we need to be able to predict optimal kernel sizes. We therefore present an advanced optimization scheme, and estimate optimal NC kernel sizes for five different patient-data sets. From the optimization results we derive a model for estimating optimal NC kernel sizes. As ground truth (GT), we used five full-volume 4D TEE patient scans, acquired with the X7-2t matrix transducer. To simulate 2D data acquisition, the GT datasets were sliced at random rotation angles and at random normalized cardiac phases. Data sets containing 400, 600, 900, 1350, and 1800 2D images were created for all patients, producing a total of 25 data sets. A 2D Gaussian function was used as NC kernel, and optimal kernel sizes were obtained with a quasi-Newton optimizer. A power law model was fitted to the optimal kernels estimated. We conclude that optimal kernel sizes for NC can be successfully predicted by a model at the cost of a relatively small increase in the reconstruction error. {\textcopyright} 2012 IEEE.},
address = {New York},
author = {Haak, Alexander and Klein, Stefan and {Van Burken}, Gerard and {De Jong}, Nico and {Van Der Steen}, Antonius F.W. and Bosch, Johannes G. and {Van Stralen}, Marijn and Pluim, Josien P.W.},
booktitle = {IEEE International Ultrasonics Symposium, IUS},
doi = {10.1109/ULTSYM.2012.0175},
isbn = {9781467345613},
issn = {19485719},
keywords = {kernel optimization,normalized convolution,quasi newton},
pages = {703--706},
publisher = {Ieee},
series = {2012 Ieee International Ultrasonics Symposium},
title = {{Optimal kernel sizes for 4D image reconstruction using normalized convolution from sparse fast-rotating transesophageal 2D ultrasound images}},
type = {Book},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84882446800{\&}doi=10.1109{\%}2FULTSYM.2012.0175{\&}partnerID=40{\&}md5=2eab7eaf8d8fbce0ab5d12917b0183ab {\%}3CGo to},
year = {2012}
}
@inproceedings{Akbarzadeh,
abstract = {Diagnosis , staging and treatment of disease depends on the morphological and functional information obtained from multimodality molecular imaging systems. The combination of functional and morphological information is now routinely performed to overcome the limitations of each individual modality. Attenuation of photons in the object under study is one of the main limitations of quantitative PET imaging. Attenuation correction plays a pivotal role in PET imaging. However, the availability of CT data on hybrid PET/CT scanners made it possible to build an accurate attenuation map. One of the well-known methods for generation of the attenuation map on PE/MRI systems is MR-based attenuation correction (MRAC) where image segmentation is used to classify MRI into several classes corresponding to different attenuation factors. In this study we investigate the effect of using different numbers of classes for the generation of attenuation maps on the accuracy of attenuation correction of PET data. The study was carried out using simulations of the XCAT phantom and 10 clinical studies. For the later, CT and PET images of 10 patients were used with CT-based attenuation correction assumed as reference. MRI was classified into different classes to produce two, three and four-class attenuation maps using the ITK library. The relative error showed that the lower number of classes will increase the global error over 8{\%}. The elimination of bony structures from the attenuation map will cause a local error over 3{\%}. In clinical studies, SUV mean and SUVmax were calculated for each AC method. The results seem to indicate an underestimation of 11{\%} because of neglecting bone. {\textcopyright} 2011 IEEE.},
address = {New York},
author = {Akbarzadeh, A. and Ay, M. R. and Ahmadian, A. and {Riahi Alam}, N. and Zaidi, H.},
booktitle = {IEEE Nuclear Science Symposium Conference Record},
doi = {10.1109/NSSMIC.2011.6152682},
isbn = {9781467301183},
issn = {10957863},
pages = {2524--2530},
publisher = {Ieee},
series = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
title = {{Impact of using different tissue classes on the accuracy of MR-based attenuation correction in PET-MRI}},
type = {Book Section},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858681408{\&}doi=10.1109{\%}2FNSSMIC.2011.6152682{\&}partnerID=40{\&}md5=cb5e411de14cb1afbdf27ca41e4b2746},
year = {2011}
}
@inproceedings{Fishbaugh2018a,
abstract = {Statistical shape analysis captures the geometric properties of a given set of shapes, obtained from medical images, by means of statistical methods. Orthognathic surgery is a type of craniofacial surgery that is aimed at correcting severe skeletal deformities in the mandible and maxilla. Methods assuming spherical topology cannot represent the class of anatomical structures exhibiting complex geometries and topologies, including the mandible. In this paper we propose methodology based on non-rigid deformations of 3D geometries to be applied to objects with thin, complex structures. We are able to accurately and quantitatively characterize bone healing at the osteotomy site as well as condylar remodeling for three orthognathic surgery cases, demonstrating the effectiveness of the proposed methodology.},
address = {New York},
author = {Fishbaugh, James and Pascal, Laura and Fischer, Luke and Nguyen, Tung and Boen, Celso and Goncalves, Joao and Gerig, Guido and Paniagua, Beatriz},
booktitle = {Proceedings - International Symposium on Biomedical Imaging},
doi = {10.1109/ISBI.2018.8363742},
isbn = {9781538636367},
issn = {19458452},
keywords = {Complex topology,Diffeomorphic shape registration,Orthognathic surgery,Statistical shape analysis,Statistical shape modeling},
month = {apr},
pages = {1010--1013},
publisher = {Ieee},
series = {IEEE International Symposium on Biomedical Imaging},
title = {{Estimating shape correspondence for populations of objects with complex topology}},
type = {Book Section},
url = {https://ieeexplore.ieee.org/document/8363742/ {\%}3CGo to},
volume = {2018-April},
year = {2018}
}
@inproceedings{Schiwarth2018,
abstract = {Fiber-reinforced polymers (FRPs) are of great importance in various industries because of their superior properties as compared to conventional materials, their versatile processing, and their wide application possibilities. To fulfil the high-quality standards in its respective applications, industrial 3D X-ray computed tomography (XCT) is increasingly used. It enables an accurate, non-destructive characterization of material features such as inclusions, voids, fibers, or other reinforcements, which is of core importance for material and component design. In this work we present FeatureAnalyzer, a generalization of the previously introduced PorosityAnalyzer tool, which allows to analyze dataset series as generated for exploring the parameter space of image processing workflows (including pre-filtering, segmentation, postprocessing or quantification) applied to XCT datasets of fiber-reinforced polymers. With a scatter plot matrix (SPLOM), the characteristics of the features of interest may be examined in more detail regarding the used input and output parameters. Individual results may be selected in the SPLOM and analyzed using 2D slice views and 3D renderings. For this work, three different samples (sample {\#}1 - {\#}3) were scanned by means of XCT and were evaluated by using FeatureAnalyzer. The samples {\#}1 and {\#}2 have a porosity value of approximately 1.7 vol. {\%}. By using the FeatureAnalyzer in combination with SPLOM, the threshold parameters could be analyzed before the over-segmentation of voids occurs. Additional evaluations by parallel coordinates clearly show, that sample {\#}2 has a higher number of spherical voids in the center of the specimen compared to sample {\#}1. By evaluating the resin content of sample {\#}3, the individual layer thickness could be measured. The source code of the tool is available on Github: https://github.com/3dct/open-iA/},
address = {Bristol},
author = {Schiwarth, M. and Weissenb{\"{o}}ck, J. and Plank, B. and Fr{\"{o}}hler, B. and Heinzl, C. and Kastner, J.},
booktitle = {IOP Conference Series: Materials Science and Engineering},
doi = {10.1088/1757-899X/406/1/012014},
issn = {1757899X},
number = {1},
publisher = {Iop Publishing Ltd},
series = {IOP Conference Series-Materials Science and Engineering},
title = {{Visual analysis of void and reinforcement characteristics in X-ray computed tomography dataset series of fiber-reinforced polymers}},
type = {Book Section},
url = {{\%}3CGo to https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054221856{\&}doi=10.1088{\%}2F1757-899X{\%}2F406{\%}2F1{\%}2F012014{\&}partnerID=40{\&}md5=e1757458a87eb396d4743ad19f658d5a},
volume = {406},
year = {2018}
}
@article{johnson2015itk,
abstract = {The Insight Toolkit (ITK) is an open-source software toolkit for performing registration and segmen- tation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired fromsuchmedical instru- mentation as CT orMRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in themedical environment, a CT scan may be aligned with aMRI scan in order to combine the information contained in both.},
author = {Johnson, Hans J. and McCormick, Matthew M and Ibanez, Luis},
isbn = {978-1930934276},
journal = {Kitware, Inc.(January 2015)},
keywords = {Guide,Registration,Segmentation},
publisher = {Kitware, Inc.},
title = {{The ITK Software Guide Book 1: Introduction and Development Guidelines Fourth Edition Updated for ITK version 4.7}},
url = {https://itk.org/},
year = {2015}
}
@article{Johnson2018,
abstract = {A robust fully automated algorithm for identifying an arbitrary number of landmark points in the human brain is described and validated. The proposed method combines statistical shape models with trained brain morphometric measures to estimate midbrain landmark positions reliably and accurately. Gross morphometric constraints provided by automatically identified eye centers and the center of the head mass are shown to provide robust initialization in the presence of large rotations in the initial head orientation. Detection of primary midbrain landmarks are used as the foundation from which extended detection of an arbitrary set of secondary landmarks in different brain regions by applying a linear model estimation and principle component analysis. This estimation model sequentially uses the knowledge of each additional detected landmark as an improved foundation for improved prediction of the next landmark location. The accuracy and robustness of the presented method was evaluated by comparing the automatically generated results to two manual raters on 30 identified landmark points extracted from each of 30 T1-weighted magnetic resonance images. For the landmarks with unambiguous anatomical definitions, the average discrepancy between the algorithm results and each human observer differed by less than 1 mm from the average inter-observer variability when the algorithm was evaluated on imaging data collected from the same site as the model building data. Similar results were obtained when the same model was applied to a set of heterogeneous image volumes from seven different collection sites representing 3 scanner manufacturers. This method is reliable for general application in large-scale multi-site studies that consist of a variety of imaging data with different orientations, spacings, origins, and field strengths.},
author = {Ghayoor, Ali and Vaidya, Jatin G. and Johnson, Hans J.},
doi = {10.1016/j.neuroimage.2017.04.012},
file = {:Users/johnsonhj/Documents/Mendeley Desktop/Ghayoor, Vaidya, Johnson/NeuroImage/Ghayoor, Vaidya, Johnson - 2018 - Robust automated constellation-based landmark detection in human brain imaging.pdf:pdf},
issn = {10959572},
journal = {NeuroImage},
keywords = {Automated landmark detection,Morphometric measures,Principle component analysis,Statistical shape models},
pages = {471--481},
title = {{Robust automated constellation-based landmark detection in human brain imaging}},
volume = {170},
year = {2018}
}
@incollection{Avants2012,
abstract = {Publicly available scientific resources help establish evaluation standards, provide a platform for teaching and may improve reproducibility. Version 4 of the Insight ToolKit ( ITK ) seeks to establish new standards in publicly available image registration methodology. In this work, we provide an overview and preliminary evaluation of the revised toolkit against registration based on the previous major ITK version (3.20). Furthermore, we propose a nomenclature that may be used to discuss registration frameworks via schematic representations. In total, the ITK 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. {\textcopyright} 2012 Springer-Verlag.},
annote = {From Duplicate 2 (A unified image registration framework for ITK - Avants, Brian B.; Tustison, Nicholas J.; Song, Gang; Wu, Baohua; Stauffer, Michael; McCormick, Matthew M.; Johnson, Hans J.; Gee, James C.)

From Duplicate 1 (A unified image registration framework for ITK - Avants, Brian B.; Tustison, Nicholas J.; Song, Gang; Wu, Baohua; Stauffer, Michael; McCormick, Matthew M.; Johnson, Hans J.; Gee, James C.)

From Duplicate 1 (A unified image registration framework for ITK - Avants, Brian B.; Tustison, Nicholas J.; Song, Gang; Wu, Baohua; Stauffer, Michael; McCormick, Matthew M.; Johnson, Hans J.; Gee, James C.)

{\#}{\#}CONTRIBUTIONS: As a member of ITK development team, I worked closely to develop, test, and implement the registration frameworks described in this work.:{\#}{\#}
{\#}{\#}JOURNAL{\_}TYPE: Conference :{\#}{\#}

From Duplicate 2 (A unified image registration framework for ITK - Avants, Brian B.; Tustison, Nicholas J.; Song, Gang; Wu, Baohua; Stauffer, Michael; McCormick, Matthew M.; Johnson, Hans J.; Gee, James C.)

From Duplicate 2 (A unified image registration framework for ITK - Avants, Brian B.; Tustison, Nicholas J.; Song, Gang; Wu, Baohua; Stauffer, Michael; McCormick, Matthew M.; Johnson, Hans J.; Gee, James C.)

From Duplicate 1 (A unified image registration framework for ITK - Avants, Brian B.; Tustison, Nicholas J.; Song, Gang; Wu, Baohua; Stauffer, Michael; McCormick, Matthew M.; Johnson, Hans J.; Gee, James C.)

{\#}{\#}CONTRIBUTIONS: As a member of ITK development team, I worked closely to develop, test, and implement the registration frameworks described in this work.:{\#}{\#}
{\#}{\#}JOURNAL{\_}TYPE: Conference :{\#}{\#}},
author = {Avants, Brian B. and Tustison, Nicholas J. and Song, Gang and Wu, Baohua and Stauffer, Michael and McCormick, Matthew M. and Johnson, Hans J. and Gee, James C.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
chapter = {A Unified},
doi = {10.1007/978-3-642-31340-0_28},
edition = {5th Intern},
editor = {{Dawant, B.; Christensen, G.E.; Fitzpatrick, J.M.; Rueckert}, D (Eds.},
file = {:Users/johnsonhj/Documents/Mendeley Desktop/Avants et al/Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)/Avants et al. - 2012 - A unified image registration framework for ITK.pdf:pdf},
isbn = {9783642313394},
issn = {03029743},
number = {LNCS 7359},
organization = {Springer Berlin Heidelberg},
pages = {266--275},
publisher = {Springer Berlin Heidelberg},
title = {{A unified image registration framework for ITK}},
url = {http://link.springer.com/10.1007/978-3-642-31340-0{\_}28 http://link.springer.com/chapter/10.1007{\%}2F978-3-642-31340-0{\_}28 http://link.springer.com/chapter/10.1007{\%}252F978-3-642-31340-0{\_}28},
volume = {7359 LNCS},
year = {2012}
}
@article{forbes2016open,
abstract = {The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools

license_type: permissive

branch_name: refs/heads/master

extension: bib