text:
, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor.
CONCLUSION: The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.},
author = {Lok, Ka Hei and Shi, Lin and Zhu, Xianlun and Wang, Defeng},
doi = {10.3233/XST-17261},
issn = {10959114},
journal = {Journal of X-ray science and technology},
keywords = {Brain tumor segmentation,Selective Binary Gaussian Filtering Regularizing L,Singed Pressure Force (SPF),evaluation of tumor segmentation accuracy},
number = {2},
pages = {301--312},
title = {{Fast and robust brain tumor segmentation using level set method with multiple image information}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {25},
year = {2017}
}
@incollection{Loyek2011,
abstract = {Life science research aims at understanding the relationships in genomics, proteomics and metabolomics on all levels of biological self organization, dealing with data of increasing dimension and complexity. Bioimages represent a new data domain in this context, gaining growing attention since it closes important gaps left by the established molecular techniques. We present a new, web-based strategy that allows a new way of collaborative bioimage interpretaion through knowledge integration. We show, how this can be supported by combining data mining algorithms running on powerful compute servers and a next generation rich internet application (RIA) front-end offering database/project management and high-level tools for exploratory data analysis and annotation. We demonstrate our system BioIMAX using a bioimage dataset from High-Content Screening experiments to study bacterial infection in cell cultures. {\textcopyright} 2011 Springer-Verlag.},
author = {Loyek, Christian and K{\"{o}}lling, Jan and Langenk{\"{a}}mper, Daniel and Niehaus, Karsten and Nattkemper, Tim W.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-24800-9_25},
isbn = {9783642247996},
issn = {03029743},
keywords = {Bioimage Informatics,Data Mining,Exploratory Data Analysis,High-content screening,Information Visualization,Life Science,Rich Internet Application,Semantic Annotation,Web2.0},
pages = {258--269},
title = {{A Web2.0 strategy for the collaborative analysis of complex bioimages}},
type = {Serial},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80455129929{\&}doi=10.1007{\%}2F978-3-642-24800-9{\_}25{\&}partnerID=40{\&}md5=14d944bb2916a977fa416b20b12387e3},
volume = {7014 LNCS},
year = {2011}
}
@article{Loyek2011a,
abstract = {Background: Innovations in biological and biomedical imaging produce complex high-content and multivariate image data. For decision-making and generation of hypotheses, scientists need novel information technology tools that enable them to visually explore and analyze the data and to discuss and communicate results or findings with collaborating experts from various places.Results: In this paper, we present a novel Web2.0 approach, BioIMAX, for the collaborative exploration and analysis of multivariate image data by combining the webs collaboration and distribution architecture with the interface interactivity and computation power of desktop applications, recently called rich internet application.Conclusions: BioIMAX allows scientists to discuss and share data or results with collaborating experts and to visualize, annotate, and explore multivariate image data within one web-based platform from any location via a standard web browser requiring only a username and a password. BioIMAX can be accessed at http://ani.cebitec.uni-bielefeld.de/BioIMAX with the username "test" and the password "test1" for testing purposes. {\textcopyright} 2011 Loyek et al; licensee BioMed Central Ltd.},
author = {Loyek, Christian and Rajpoot, Nasir M. and Khan, Michael and Nattkemper, Tim W.},
doi = {10.1186/1471-2105-12-297},
issn = {14712105},
journal = {BMC Bioinformatics},
pages = {11},
title = {{BioIMAX: A Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {12},
year = {2011}
}
@article{Lucas2010,
abstract = {Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development, that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Javabased rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. Hie system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Infoimatics Tools and Resources Clearinghouse (NITRC). {\textcopyright} Springer Science+Business Media, LLC 2010.},
author = {Lucas, Blake C. and Bogovic, John A. and Carass, Aaron and Bazin, Pierre Louis and Prince, Jerry L. and Pham, Dzung L. and Landman, Bennett A.},
doi = {10.1007/s12021-009-9061-2},
issn = {15392791},
journal = {Neuroinformatics},
keywords = {Image processing,MRI,Parallel processing,Pipeline,Rapid prototyping},
number = {1},
pages = {5--17},
title = {{The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {8},
year = {2010}
}
@article{Ma2019,
abstract = {Iodine-125 seed brachytherapy has great potential in the treatment of malignant tumors. However, the success of this treatment is highly dependent on the ability to accurately position the coplanar template. The aim of this study was to develop an auto-positioning system for the template with a design focus on efficiency and accuracy. In this study, an auto-positioning system was presented, which was composed of a treatment planning system (TPS) and a robot-assisted system. The TPS was developed as a control system for the robot-assisted system. Then, the robot-assisted system was driven by the output of the TPS to position the template. Contrast experiments for error validation were carried out in a computed tomography environment to compare with the traditional positioning method (TPM). Animal experiments on Sprague–Dawley rats were also carried out to evaluate the auto-positioning system. The error validation experiments and animal experiments with this auto-positioning system were successfully carried out with improved efficiency and accuracy. The error validation experiments achieved a positioning error of 1.04 ± 0.19 mm and a positioning time of 23.15 ± 2.52 min, demonstrating a great improvement compared with the TPM (2.55 ± 0.21 mm and 40.35 ± 2.99 min, respectively). The animal experiments demonstrated that the mean deviation of the seed position was 0.75 mm. The dose-volume histogram of the preoperative planning showed the same as the postoperative dosimetry validation. A novel auto-positioning system driven by preoperative planning was established, which exhibited higher efficiency and accuracy compared with the TPM.},
author = {Ma, Xiaodong and Yang, Zhiyong and Jiang, Shan and Zhang, Guobin and Chai, Shude},
doi = {10.1002/acm2.12591},
issn = {15269914},
journal = {Journal of Applied Clinical Medical Physics},
keywords = {auto-positioning,iodine-125 seed brachytherapy,preoperative planning,treatment planning system},
number = {6},
pages = {23--30},
title = {{A novel auto-positioning method in Iodine-125 seed brachytherapy driven by preoperative planning}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {20},
year = {2019}
}
@article{Ma2019a,
abstract = {Purpose: An ideal dose distribution in a target is the ultimate goal of preoperative dose planning. Furthermore, avoiding vital organs or tissues such as blood vessels or bones during the puncture procedure is significant in lowdose-rate brachytherapy. The aim of this work is to develop a hybrid inverse optimization method based on non-coplanar needles to assist the physician during conformal dose planning, which cannot be properly achieved with a traditional coplanar template. Material and methods: The hybrid inverse optimization technique include two novel technologies: an inverse optimization algorithm and a dose volume histogram evaluation method. Brachytherapy treatment planning system was designed as an experimental platform. Left lung adenocarcinoma case was used to test the performance of the method in non-coplanar and coplanar needles, and malignant tumor of spine case was involved to test the practical application of this technique. In addition, the optimization time of every test was also recorded. Results: The proposed method can achieve an ideal dose distribution, avoiding vital organs (bones). In the first experiment, 13 non-coplanar needles and 24 seeds were used to get an ideal dose distribution to cover the target, whereas 11 coplanar needles and 23 seeds were used to cover the same target. In the second experiment, the new method used 22 non-coplanar needles and 65 seeds to cover the target, while 63 seeds and 22 needles were used in the actual operation. In addition, the computation time of the hybrid inverse optimization method was 20.5 seconds in the tumor of 94.67 cm3 by using 22 needles, which was fast enough for clinical application. Conclusions: The hybrid inverse optimization method achieved high conformity in the clinical practice. The non-coplanar needle can help to achieve a better dose distribution than the coplanar needle.},
author = {Ma, Xiaodong and Yang, Zhiyong and Jiang, Shan and Zhang, Guobin and Huo, Bin and Chai, Shude},
doi = {10.5114/jcb.2019.86167},
issn = {20812841},
journal = {Journal of Contemporary Brachytherapy},
keywords = {Brachytherapy,Dose volume histogram,Inverse optimization,Non-coplanar needle},
number = {3},
pages = {267--279},
title = {{Hybrid optimization based on non-coplanar needles for brachytherapy dose planning}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {11},
year = {2019}
}
@inbook{Macia2012,
abstract = {Accurate detection and extraction of 3D vascular structures is a crucial step for many medical image applications that require vascular analysis. Vessel tracking algorithms iteratively follow vascular branches point by point, obtaining geometric descriptors, such as centerlines and sections of branches, that describe patient-specific vasculature. In order to obtain these descriptors, most approaches use specialized scaled vascular feature detectors. However, these detectors may fail due to the presence of nearby spurious structures, incorrect scale or parameter choice or other undesired effects, obtaining incorrect local sections which may lead to unrecoverable errors during the tracking procedure. We propose to combine this approach with an evolutionary optimization framework that use specific modified vascular detectors as cost functions in order to obtain accurate vascular sections when the direct detection approach fails. We demonstrate the validity of this new approach with experiments using real datasets. We also show that, for a family of medialness functions, the procedure can be performed at fixed small scales which is computationally efficient for local kernel-based estimators. {\textcopyright} 2012 Springer-Verlag.},
address = {Berlin},
author = {Mac{\'{i}}a, Iv{\'{a}}n and Gra{\~{n}}a, Manuel},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-28931-6_48},
editor = {Corchado, E and Snasel, V and Abraham, A and Wozniak, M and Grana, M and Cho, S B},
isbn = {9783642289309},
issn = {03029743},
keywords = {Evolutionary Optimization,Feature Detectors,Medialness,Medical Image Analysis,Section Estimator,Vascular Analysis,Vascular Tracking,Vesselness,Vessels},
number = {PART 2},
pages = {503--513},
publisher = {Springer-Verlag Berlin},
series = {Lecture Notes in Computer Science},
title = {{Vascular section estimation in medical images using combined feature detection and evolutionary optimization}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {7209 LNAI},
year = {2012}
}
@incollection{Macia2012a,
abstract = {Accurate detection and extraction of 3D vascular structures is a crucial step for many medical image applications that require vascular analysis. Vessel tracking algorithms iteratively follow vascular branches point by point, obtaining geometric descriptors, such as centerlines and sections of branches, that describe patient-specific vasculature. In order to obtain these descriptors, most approaches use specialized scaled vascular feature detectors. However, these detectors may fail due to the presence of nearby spurious structures, incorrect scale or parameter choice or other undesired effects, obtaining incorrect local sections which may lead to unrecoverable errors during the tracking procedure. We propose to combine this approach with an evolutionary optimization framework that use specific modified vascular detectors as cost functions in order to obtain accurate vascular sections when the direct detection approach fails. We demonstrate the validity of this new approach with experiments using real datasets. We also show that, for a family of medialness functions, the procedure can be performed at fixed small scales which is computationally efficient for local kernel-based estimators. {\textcopyright} 2012 Springer-Verlag.},
author = {Mac{\'{i}}a, Iv{\'{a}}n and Gra{\~{n}}a, Manuel},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-28931-6_48},
isbn = {9783642289309},
issn = {03029743},
keywords = {Evolutionary Optimization,Feature Detectors,Medialness,Medical Image Analysis,Section Estimator,Vascular Analysis,Vascular Tracking,Vesselness,Vessels},
number = {PART 2},
pages = {503--513},
title = {{Vascular section estimation in medical images using combined feature detection and evolutionary optimization}},
type = {Serial},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858807369{\&}doi=10.1007{\%}2F978-3-642-28931-6{\_}48{\&}partnerID=40{\&}md5=1574b66250aeb6a43bb8a54db03d91e3},
volume = {7209 LNAI},
year = {2012}
}
@inbook{Macia2010,
abstract = {We propose the development of a knowledge representation model in the area of Blood Vessel analysis, whose need we feel for the future development of the field and for our own research efforts. It will allow easy reuse of software pieces through appropriate abstractions, facilitating the development of innovative methods, procedures and applications. In this paper we present some key ideas that will be fully developed elsewhere. {\textcopyright} Springer-Verlag 2010.},
address = {Berlin},
author = {Mac{\'{i}}a, I. and Gra{\~{n}}a, M. and Paloc, C.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-15384-6_9},
editor = {Setchi, R and Jordanov, I and Howlett, R J and Jain, L C},
isbn = {3642153836},
issn = {03029743},
number = {PART 4},
pages = {80--87},
publisher = {Springer-Verlag Berlin},
series = {Lecture Notes in Artificial Intelligence},
title = {{Towards a proposal for a vessel knowledge representation model}},
type = {Book Section},
url = {{\%}3CGo to},
volume = {6279 LNAI},
year = {2010}
}
@article{Macia2012b,
abstract = {We have detected the lack of a widely accepted knowledge representation model in the area of Blood Vessel analysis. We find that such a tool is needed for the future development of the field and our own research efforts. It will allow easy reuse of software pieces through appropriate abstractions, facilitating the development of innovative methods, procedures and applications. We include a thorough review of vascular morphology image analysis. After the identification of the key representation elements and operations, we propose a Vessel Knowledge Representation (VKR) model that would fill this gap. We give insights into its implementation based on standard Object-Oriented Programming tools and paradigms. The VKR would easily integrate with existing medical imaging and visualization software platforms, such as the Insight ToolKit (ITK) and Visualization Toolkit (VTK). {\textcopyright} 2011 Springer-Verlag London Limited.},
author = {Mac{\'{i}}a, Iv{\'{a}}n and Gra{\~{n}}a, Manuel and Paloc, Celine},
doi = {10.1007/s10115-010-0377-x},
issn = {02191377},
journal = {Knowledge and Information Systems},
keywords = {Knowledge representation,Medical image,Vessel analysis},
number = {2},
pages = {457--491},
title = {{Knowledge management in image-based analysis of blood vessel structures}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {30},
year = {2012}
}
@incollection{Macia2010a,
abstract = {We propose the development of a knowledge representation model in the area of Blood Vessel analysis, whose need we feel for the future development of the field and for our own research efforts. It will allow easy reuse of software pieces through appropriate abstractions, facilitating the development of innovative methods, procedures and applications. In this paper we present some key ideas that will be fully developed elsewhere. {\textcopyright} Springer-Verlag 2010.},
author = {Mac{\'{i}}a, I. and Gra{\~{n}}a, M. and Paloc, C.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-15384-6_9},
isbn = {3642153836},
issn = {03029743},
number = {PART 4},
pages = {80--87},
title = {{Towards a proposal for a vessel knowledge representation model}},
type = {Serial},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649239965{\&}doi=10.1007{\%}2F978-3-642-15384-6{\_}9{\&}partnerID=40{\&}md5=0484a83cf98f28846128f6c2d221cffd},
volume = {6279 LNAI},
year = {2010}
}
@article{Maga2017,
abstract = {Laboratory mice are staples for evo/devo and genetics studies. Inbred strains provide a uniform genetic background to manipulate and understand gene–environment interactions, while their crosses have been instrumental in studies of genetic architecture, integration and modularity, and mapping of complex biological traits. Recently, there have been multiple large-scale studies of laboratory mice to further our understanding of the developmental basis, evolution, and genetic control of shape variation in the craniofacial skeleton (i.e. skull and mandible). These experiments typically use micro-computed tomography (micro-CT) to capture the craniofacial phenotype in 3D and rely on manually annotated anatomical landmarks to conduct statistical shape analysis. Although the common choice for imaging modality and phenotyping provides the potential for collaborative research for even larger studies with more statistical power, the investigator (or lab-specific) nature of the data collection hampers these efforts. Investigators are rightly concerned that subtle differences in how anatomical landmarks were recorded will create systematic bias between studies that will eventually influence scientific findings. Even if researchers are willing to repeat landmark annotation on a combined dataset, different lab practices and software choices may create obstacles for standardization beyond the underlying imaging data. Here, we propose a freely available analysis system that could assist in the standardization of micro-CT studies in the mouse. Our proposal uses best practices developed in biomedical imaging and takes advantage of existing open-source software and imaging formats. Our first contribution is the creation of a synthetic template for the adult mouse craniofacial skeleton from 25 inbred strains and five F1 crosses that are widely used in biological research. The template contains a fully segmented cranium, left and right hemi-mandibles, endocranial space, and the first few cervical vertebrae. We have been using this template in our lab to segment and isolate cranial structures in an automated fashion from a mixed population of mice, including craniofacial mutants, aged 4–12.5 weeks. As a secondary contribution, we demonstrate an application of nearly automated shape analysis, using symmetric diffeomorphic image registration. This approach, which we call diGPA, closely approximates the popular generalized Procrustes analysis (GPA) but negates the collection of anatomical landmarks. We achieve our goals by using the open-source advanced normalization tools (ANT) image quantification library, as well as its associated R library (ANTsR) for statistical image analysis. Finally, we make a plea to investigators to commit to using open imaging standards and software in their labs to the extent possible to increase the potential for data exchange and improve the reproducibility of findings. Future work will incorporate more anatomical detail (such as individual cranial bones, turbinals, dentition, middle ear ossicles) and more diversity into the template.},
author = {Maga, A. Murat and Tustison, Nicholas J. and Avants, Brian B.},
doi = {10.1111/joa.12645},
issn = {14697580},
journal = {Journal of Anatomy},
keywords = {geometrics morphometrics,image processing,image-based shape analysis,landmarking,microCT,segmentation},
number = {3},
pages = {433--443},
title = {{A population level atlas of Mus musculus craniofacial skeleton and automated image-based shape analysis}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {231},
year = {2017}
}
@inproceedings{Magnain,
abstract = {Optical coherence tomography visualizes the structure of the human brain, from the cortical laminar structure to the individual neurons.},
author = {Magnain, Caroline and Augustinack, Jean C. and Konukoglu, Ender and Boas, David and Fischl, Bruce},
booktitle = {Optics and the Brain, BRAIN 2015},
doi = {10.1364/brain.2015.brt4b.5},
isbn = {9781557529541},
title = {{Visualization of the cytoarchitecture of Ex vivo human brain by optical coherence tomography}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930804493{\&}partnerID=40{\&}md5=a7e7e7e3b1f380d82e3ea7c3f1960a06},
year = {2015}
}
@article{Magnain2015,
abstract = {Abstract. The cytoarchitecture of the human brain is of great interest in diverse fields: neuroanatomy, neurology, neuroscience, and neuropathology. Traditional histology is a method that has been historically used to assess cell and fiber content in the ex vivo human brain. However, this technique suffers from significant distortions. We used a previously demonstrated optical coherence microscopy technique to image individual neurons in several square millimeters of en-face tissue blocks from layer II of the human entorhinal cortex, over 50 $\mu$min depth. The same slices were then sectioned and stained for Nissl substance. We registered the optical coherence tomog- raphy (OCT) images with the corresponding Nissl stained slices using a nonlinear transformation. The neurons were then segmented in both images and we quantified the overlap. We show that OCT images contain infor- mation about neurons that is comparable to what can be obtained from Nissl staining, and thus can be used to assess the cytoarchitecture of the ex vivo human brain with minimal distortion. With the future integration of a vibratome into the OCT imaging rig, this technique can be scaled up to obtain undistorted volumetric data of centimeter cube tissue blocks in the near term, and entire human hemispheres in the future.},
author = {Magnain, Caroline and Augustinack, Jean C. and Konukoglu, Ender and Frosch, Matthew P. and Sakad{\v{z}}ic, Sava and Varjabedian, Ani and Garcia, Nathalie and Wedeen, Van J. and Boas, David A. and Fischl, Bruce},
doi = {10.1117/1.nph.2.1.015004},
issn = {2329-423X},
journal = {Neurophotonics},
number = {1},
pages = {015004},
title = {{Optical coherence tomography visualizes neurons in human entorhinal cortex}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {2},
year = {2015}
}
@article{Magnain2019,
abstract = {Optical coherence tomography is an optical technique that uses backscattered light to highlight intrinsic structure, and when applied to brain tissue, it can resolve cortical layers and fiber bundles. Optical coherence microscopy (OCM) is higher resolution (i.e., 1.25 µm) and is capable of detecting neurons. In a previous report, we compared the correspondence of OCM acquired imaging of neurons with traditional Nissl stained histology in entorhinal cortex layer II. In the current method-oriented study, we aimed to determine the colocalization success rate between OCM and Nissl in other brain cortical areas with different laminar arrangements and cell packing density. We focused on two additional cortical areas: medial prefrontal, pre-genual Brodmann area (BA) 32 and lateral temporal BA 21. We present the data as colocalization matrices and as quantitative percentages. The overall average colocalization in OCM compared to Nissl was 67{\%} for BA 32 (47{\%} for Nissl colocalization) and 60{\%} for BA 21 (52{\%} for Nissl colocalization), but with a large variability across cases and layers. One source of variability and confounds could be ascribed to an obscuring effect from large and dense intracortical fiber bundles. Other technical challenges, including obstacles inherent to human brain tissue, are discussed. Despite limitations, OCM is a promising semi-high throughput tool for demonstrating detail at the neuronal level, and, with further development, has distinct potential for the automatic acquisition of large databases as are required for the human brain.},
author = {Magnain, Caroline and Augustinack, Jean C. and Tirrell, Lee and Fogarty, Morgan and Frosch, Matthew P. and Boas, David and Fischl, Bruce and Rockland, Kathleen S.},
doi = {10.1007/s00429-018-1777-z},
issn = {18632661},
journal = {Brain Structure and Function},
keywords = {Human brain,Isocortex,Limbic,Neuron,Optical imaging,Tissue,Validation},
number = {1},
pages = {351--362},
title = {{Colocalization of neurons in optical coherence microscopy and Nissl-stained histology in Brodmann's area 32 and area 21}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {224},
year = {2019}
}
@article{Maier2013,
abstract = {Purpose: In the community of x-ray imaging, there is a multitude of tools and applications that are used in scientific practice. Many of these tools are proprietary and can only be used within a certain lab. Often the same algorithm is implemented multiple times by different groups in order to enable comparison. In an effort to tackle this problem, the authors created CONRAD, a software framework that provides many of the tools that are required to simulate basic processes in x-ray imaging and perform image reconstruction with consideration of nonlinear physical effects. Methods: CONRAD is a Java-based state-of-the-art software platform with extensive documentation. It is based on platform-independent technologies. Special libraries offer access to hardware acceleration such as OpenCL. There is an easy-to-use interface for parallel processing. The software package includes different simulation tools that are able to generate up to 4D projection and volume data and respective vector motion fields. Well known reconstruction algorithms such as FBP, DBP, and ART are included. All algorithms in the package are referenced to a scientific source. Results: A total of 13 different phantoms and 30 processing steps have already been integrated into the platform at the time of writing. The platform comprises 74.000 nonblank lines of code out of which 19{\%} are used for documentation. The software package is available for download at http://conrad.stanford.edu. To demonstrate the use of the package, the authors reconstructed images from two different scanners, a table top system and a clinical C-arm system. Runtimes were evaluated using the RabbitCT platform and demonstrate state-of-the-art runtimes with 2.5 s for the 256 problem size and 12.4 s for the 512 problem size. Conclusions: As a common software framework, CONRAD enables the medical physics community to share algorithms and develop new ideas. In particular this offers new opportunities for scientific collaboration and quantitative performance comparison between the methods of different groups. {\textcopyright} 2013 American Association of Physicists in Medicine.},
author = {Maier, Andreas and Hofmann, Hannes G. and Berger, Martin and Fischer, Peter and Schwemmer, Chris and Wu, Haibo and M{\"{u}}ller, Kerstin and Hornegger, Joachim and Choi, Jang Hwan and Riess, Christian and Keil, Andreas and Fahrig, Rebecca},
doi = {10.1118/1.4824926},
issn = {00942405},
journal = {Medical Physics},
keywords = {C-arm computed tomography (CT),GPU,cone-beam,hardware acceleration,open-source,software frameworks},
number = {11},
pages = {8},
title = {{CONRAD - A software framework for cone-beam imaging in radiology}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {40},
year = {2013}
}
@inproceedings{Marisaldi,
abstract = {We study the possibility to use Single Photon Avalanche Diodes (SPADs) optically coupled to scintillating fibers as a novel type of gamma-ray detector for space applications. SPADs are silicon devices operating under polarization conditions above the junction breakdown voltage (typical overvoltage of 5V), for which a single photon interacting in the active region is sufficient to trigger a self sustainable avalanche discharge. SPADs can thus be used for the detection of very low light levels with an absolute timing accuracy of about 30 ps for single photon detection, without spectroscopic capabilities. In this presentation we report the preliminary results on large area SPAD (actual results refers to SPADs having 200 $\mu$m diameter, with the aim to grow up to 500 $\mu$m SPADs) coupled to scintillating fibers as the basic module for a particle tracker for space application. Dark counts rate as low as few tens of kHz at room temperature, lowering down to few kHz at -10°C have been obtained for the 200 $\mu$m devices, in accordance with the basic requirements for the proposed application. Similar instruments based on silicon photomultiplier (SiPM) readout have already been studied, but none based on SPAD has been realized up to now. Moreover, since very few information is available on SPADs for the use in a space environment, we performed bulk damage and total dose radiation tests with protons and gamma-rays in order to evaluate their radiation hardness properties and their suitability for application in a Low Earth Orbit (LEO) space mission. With this aim the SPAD devices have be irradiated using up to 20 krad total dose with gamma-rays and 5 krad with protons. {\textcopyright} 2011 IEEE.},
author = {Marisaldi, Martino and MacCagnani, Piera and Moscatelli, Francesco and Labanti, Claudio and Fuschino, Fabio and Prest, Michela and Berra, Alessandro and Bolognini, Davide and Ghioni, Massimo and Rech, Ivan and Gulinatti, Angelo and Giudice, Andrea and Simmerle, Georg and Rubini, Danilo and Candelori, Andrea and Mattiazzo, Serena},
booktitle = {IEEE Nuclear Science Symposium Conference Record},
doi = {10.1109/NSSMIC.2011.6154465},
isbn = {9781467301183},
issn = {10957863},
pages = {129--134},
title = {{Single Photon Avalanche Diodes for space applications}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858651704{\&}doi=10.1109{\%}2FNSSMIC.2011.6154465{\&}partnerID=40{\&}md5=9e403fad320eec958f118ac47b0d92e4},
year = {2011}
}
@article{Mattonen2014,
abstract = {Purpose: Benign computed tomography (CT) changes due to radiation induced lung injury (RILI) are common following stereotactic ablative radiotherapy (SABR) and can be difficult to differentiate from tumor recurrence. The authors measured the ability of CT image texture analysis, compared to more traditional measures of response, to predict eventual cancer recurrence based on CT images acquired within 5 months of treatment. Methods: A total of 24 lesions from 22 patients treated with SABR were selected for this study: 13 with moderate to severe benign RILI, and 11 with recurrence. Three-dimensional (3D) consolidative and ground-glass opacity (GGO) changes were manually delineated on all follow-up CT scans. Two size measures of the consolidation regions (longest axial diameter and 3D volume) and nine appearance features of the GGO were calculated: 2 first-order features [mean density and standard deviation of density (first-order texture)], and 7 second-order texture features [energy, entropy, correlation, inverse difference moment (IDM), inertia, cluster shade, and cluster prominence]. For comparison, the corresponding response evaluation criteria in solid tumors measures were also taken for the consolidation regions. Prediction accuracy was determined using the area under the receiver operating characteristic curve (AUC) and two-fold cross validation (CV). Results: For this analysis, 46 diagnostic CT scans scheduled for approximately 3 and 6 months post-treatment were binned based on their recorded scan dates into 2-5 month and 5-8 month follow-up time ranges. At 2-5 months post-treatment, first-order texture, energy, and entropy provided AUCs of 0.79-0.81 using a linear classifier. On two-fold CV, first-order texture yielded 73{\%} accuracy versus 76{\%}-77{\%} with the second-order features. The size measures of the consolidative region, longest axial diameter and 3D volume, gave two-fold CV accuracies of 60{\%} and 57{\%}, and AUCs of 0.72 and 0.65, respectively. Conclusions: Texture measures of the GGO appearance following SABR demonstrated the ability to predict recurrence in individual patients within 5 months of SABR treatment. Appearance changes were also shown to be more accurately predictive of recurrence, as compared to size measures within the same time period. With further validation, these results could form the substrate for a clinically useful computer-aided diagnosis tool which could provide earlier salvage of patients with recurrence. {\textcopyright} 2014 American Association of Physicists in Medicine.},
author = {Mattonen, Sarah A. and Palma, David A. and Haasbeek, Cornelis J.A. and Senan, Suresh and Ward, Aaron D.},
doi = {10.1118/1.4866219},
issn = {00942405},
journal = {Medical Physics},
keywords = {cancer recurrence,computed tomography,lung,stereotactic radiation therapy,texture analysis},
number = {3},
pages = {14},
title = {{Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {41},
year = {2014}
}
@article{Mattonen2015,
abstract = {Benign radiation-induced lung injury (RILI) is not uncommon following stereotactic ablative radiotherapy (SABR) for lung cancer and can be difficult to differentiate from tumor recurrence on follow-up imaging. We previously showed the ability of computed tomography (CT) texture analysis to predict recurrence. The aim of this study was to evaluate and compare the accuracy of recurrence prediction using manual region-of-interest segmentation to that of a semiautomatic approach. We analyzed 22 patients treated for 24 lesions (11 recurrences, 13 RILI). Consolidative and ground-glass opacity (GGO) regions were manually delineated. The longest axial diameter of the consolidative region on each post-SABR CT image was measured. This line segment is routinely obtained as part of the clinical imaging workflow and was used as input to automatically delineate the consolidative region and subsequently derive a periconsolidative region to sample GGO tissue. Texture features were calculated, and at two to five months post-SABR, the entropy texture measure within the semiautomatic segmentations showed prediction accuracies [areas under the receiver operating characteristic curve (AUC): 0.70 to 0.73] similar to those of manual GGO segmentations (AUC: 0.64). After integration into the clinical workflow, this decision support system has the potential to support earlier salvage for patients with recurrence and fewer investigations of benign RILI.},
author = {Mattonen, Sarah A. and Tetar, Shyama and Palma, David A. and Louie, Alexander V. and Senan, Suresh and Ward, Aaron D.},
doi = {10.1117/1.jmi.2.4.041010},
issn = {2329-4302},
journal = {Journal of Medical Imaging},
number = {4},
pages = {041010},
title = {{Imaging texture analysis for automated prediction of lung cancer recurrence after stereotactic radiotherapy}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {2},
year = {2015}
}
@inproceedings{Maule,
abstract = {This article proposes automated approach for whole brain infarction core delineation while using only non-contrast computed tomography and computed tomography angiography. The main aim is to provide additional information measuring infarction core volume while exceeding certain level is contraindication of early recanalization. Process of generation of Perfusion Blood Volume maps is described first followed by description of process of infarction core delineation. Verification of correctness is based on comparison against follow-up examinations. Discussion and future works summarizes weaknesses of the method and steps for improvement.},
author = {Maule, Petr and Kle{\v{c}}kov{\'{a}}, Jana and Rohan, Vladim{\'{i}}r},
booktitle = {KDIR 2011 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval},
doi = {10.5220/0003651704330437},
isbn = {9789898425799},
keywords = {Acute stroke,Automated infarction core segmentation,Brain ischemia,Perfusion blood volume,Volumetric maps},
pages = {433--437},
title = {{Automated approach for whole brain infarction core delineation: Using non-contrast and computed tomography angiography}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862235383{\&}partnerID=40{\&}md5=1d80a348add3d1bf8abea3228c5457a1},
year = {2011}
}
@article{McCormick2011,
abstract = {Noise artifacts due to signal decorrelation and reverberation are a considerable problem in ultrasound strain imaging. For block-matching methods, information from neighboring matching blocks has been utilized to regularize the estimated displacements. We apply a recursive Bayesian regularization algorithm developed by Hayton et al. [Artif. Intell., vol. 114, pp. 125-156, 1999] to phase-sensitive ultrasound RF signals to improve displacement estimation. The parameter of regularization is reformulated, and its meaning examined in the context of strain imaging. Tissue-mimicking experimental phantoms and RF data incorporating finite-element models for the tissue deformation and frequency-domain ultrasound simulations are used to compute the optimal parameter with respect to nominal strain and algorithmic iterations. The optimal strain regularization parameter was found to be twice the nominal strain and did not vary significantly with algorithmic iterations. The technique demonstrates superior performance over median filtering in noise reduction at strains 5 and higher for all quantitative experiments performed. For example, the strain SNR was 11 dB higher than that obtained using a median filter at 7 strain. It has to be noted that for applied deformations lower than 1, since signal decorrelation errors are minimal, using this approach may degrade the displacement image. {\textcopyright} 2010 IEEE.},
author = {McCormick, Matthew and Rubert, Nicholas and Varghese, Tomy},
doi = {10.1109/TBME.2011.2106500},
issn = {00189294},
journal = {IEEE Transactions on Biomedical Engineering},
keywords = {Bayes procedures,biomedical acoustic imaging,biomedical imaging,displacement measurement,image motion analysis,strain measurement},
number = {6},
pages = {1612--1620},
title = {{Bayesian regularization applied to ultrasound strain imaging}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956345107{\&}doi=10.1109{\%}2FTBME.2011.2106500{\&}partnerID=40{\&}md5=6d53735bfa77d8fa5f9b895224795479},
volume = {58},
year = {2011}
}
@article{McCormick2013,
abstract = {Accurate subsample displacement estimation is necessary for ultrasound elastography because of the small deformations that occur and the subsequent application of a derivative operation on local displacements. Many of the commonly used subsample estimation techniques introduce significant bias errors. This article addresses a reduced bias approach to subsample displacement estimations that consists of a two-dimensional windowed-sinc interpolation with numerical optimization. It is shown that a Welch or Lanczos window with a Nelder-Mead simplex or regular-step gradient-descent optimization is well suited for this purpose. Little improvement results from a sinc window radius greater than four data samples. The strain signal-to-noise ratio (SNR) obtained in a uniformly elastic phantom is compared with other parabolic and cosine interpolation methods; it is found that the strain SNR ratio is improved over parabolic interpolation from 11.0 to 13.6 in the axial direction and 0.7 to 1.1 in the lateral direction for an applied 1{\%} axial deformation. The improvement was most significant for small strains and displacement tracking in the lateral direction. This approach does not rely on special properties of the image or similarity function, which is demonstrated by its effectiveness with the application of a previously described regularization technique. {\textcopyright} The Author(s) 2013.},
author = {McCormick, Matthew M. and Varghese, Tomy},
doi = {10.1177/0161734613476176},
issn = {01617346},
journal = {Ultrasonic Imaging},
keywords = {motion tracking,sinc reconstruction,strain imaging,subsample interpolation},
number = {2},
pages = {76--89},
title = {{An approach to unbiased subsample interpolation for motion tracking}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {35},
year = {2013}
}
@article{McGee2011,
abstract = {The roundworm C. elegans is widely used as an aging model, with hundreds of genes identified that modulate aging (Kaeberlein et al., 2002. Mech. Ageing Dev.123, 1115-1119). The development and bodyplan of the 959 cells comprising the adult have been well described and established for more than 25years (Sulston {\&} Horvitz, 1977. Dev. Biol.56, 110-156; Sulston et al., 1983. Dev. Biol.100, 64-119.). However, morphological changes with age in this optically transparent animal are less well understood, with only a handful of studies investigating the pathobiology of aging. Age-related changes in muscle (Herndon, 2002. Nature419, 808-814), neurons (Herndon, 2002), intestine and yolk granules (Garigan, 2002. Genetics161, 1101-1112; Herndon, 2002), nuclear architecture (Haithcock, 2005. Proc. Natl Acad. Sci. USA102, 16690-16695), tail nuclei (Golden, 2007. Aging Cell6, 179-188), and the germline (Golden, 2007) have been observed via a variety of traditional relatively low-throughput methods. We report here a number of novel approaches to study the pathobiology of aging C. elegans. We combined histological staining of serial-sectioned tissues, transmission electron microscopy, and confocal microscopy with 3D volumetric reconstructions and characterized age-related morphological changes in multiple wild-type individuals at different ages. This enabled us to identify several novel pathologies with age in the C. elegans intestine, including the loss of critical nuclei, the degradation of intestinal microvilli, changes in the size, shape, and cytoplasmic contents of the intestine, and altered morphologies caused by ingested bacteria. The three-dimensional models we have created of tissues and cellular components from multiple individuals of different ages represent a unique resource to demonstrate global heterogeneity of a multicellular organism. {\textcopyright} 2011 The Authors. Aging Cell {\textcopyright} 2011 Blackwell Publishing Ltd/Anatomical Society of Great Britain and Ireland.},
author = {McGee, Matthew D. and Weber, Darren and Day, Nicholas and Vitelli, Cathy and Crippen, Danielle and Herndon, Laura A. and Hall, David H. and Melov, Simon},
doi = {10.1111/j.1474-9726.2011.00713.x},
issn = {14749718},
journal = {Aging Cell},
keywords = {Aging,C. elegans,Intestine,Microvilli,Nucleus},
number = {4},
pages = {699--710},
title = {{Loss of intestinal nuclei and intestinal integrity in aging C. elegans}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {10},
year = {2011}
}
@article{Meijs2017,
abstract = {A robust method is presented for the segmentation of the full cerebral vasculature in 4-dimensional (4D) computed tomography (CT). The method consists of candidate vessel selection, feature extraction, random forest classification and postprocessing. Image features include among others the weighted temporal variance image and parameters, including entropy, of an intensity histogram in a local region at different scales. These histogram parameters revealed to be a strong feature in the detection of vessels regardless of shape and size. The method was trained and tested on a large database of 264 patients with suspicion of acute ischemia who underwent 4D CT in our hospital in the period January 2014 to December 2015. Five subvolumes representing different regions of the cerebral vasculature were annotated in each image in the training set by medical assistants. The evaluation was done on 242 patients. A total of 16 ({\textless}8{\%}) patients showed severe under or over segmentation and were reported as failures. One out of five subvolumes was randomly annotated in 159 patients and was used for quantitative evaluation. Quantitative evaluation showed a Dice coefficient of 0.91 ± 0.07 and a modified Hausdorff distance of 0.23 ± 0.22 mm. Therefore, robust vessel segmentation in 4D CT is feasible with good accuracy.},
author = {Meijs, Midas and Patel, Ajay and {Van De Leemput}, Sil C. and Prokop, Mathias and {Van Dijk}, Ewoud J. and {De Leeuw}, Frank Erik and Meijer, Frederick J.A. and {Van Ginneken}, Bram and Manniesing, Rashindra},
doi = {10.1038/s41598-017-15617-w},
issn = {20452322},
journal = {Scientific Reports},
number = {1},
title = {{Robust Segmentation of the Full Cerebral Vasculature in 4D CT of Suspected Stroke Patients}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034432920{\&}doi=10.1038{\%}2Fs41598-017-15617-w{\&}partnerID=40{\&}md5=d67c87465788c1f4c70cc759dd0a0625},
volume = {7},
year = {2017}
}
@article{Menard2015,
abstract = {Purpose: To determine if the integration of diagnostic magnetic resonance (MR) imaging and MR-guided biopsy would improve target delineation for focal salvage therapy in men with prostate cancer.
Materials and Between September 2008 and March 2011, 30 men with bio-Methods: chemical failure after radiation therapy for prostate cancer provided written informed consent and were enrolled in a prospective clinical trial approved by the institutional research ethics board. An integrated diagnostic MR imaging and interventional biopsy procedure was performed with a 1.5-T MR imager by using a prototype table and stereotactic transperineal template. Multiparametric MR imaging (T2-weighted, dynamic contrast material-enhanced, and diffusion-weighted sequences) was followed by targeted biopsy of suspicious regions and systematic sextant sampling. Biopsy needle locations were imaged and registered to diagnostic images. Two observers blinded to clinical data and the results of prior imaging studies delineated tumor boundaries. Area under the receiver operating characteristic curve (Az) was calculated based on generalized linear models by using biopsy as the reference standard to distinguish benign from malignant lesions.
Results: Twenty-eight patients were analyzed. Most patients (n = 22) had local recurrence, with 82{\%} (18 of 22) having unifocal disease. When multiparametric volumes from two observers were combined, it increased the apparent overall tumor volume by 30{\%}; however, volumes remained small (mean, 2.9 mL; range, 0.5-8.3 mL). Tumor target boundaries differed between T2-weighted, dynamic contrast-enhanced, and diffusion-weighted sequences (mean Dice coefficient, 0.13-0.35). Diagnostic accuracy in the identification of tumors improved with a multiparametric approach versus a strictly T2-weighted or dynamic contrast-enhanced approach through an improvement in sensitivity (observer 1, 0.65 vs 0.35 and 0.44, respectively; observer 2, 0.82 vs 0.64 and 0.53, respectively; P {\textless} .05) and improved further with a 5-mm expansion margin (Az = 0.85 vs 0.91 for observer 2). After excluding three patients with fewer than six informative biopsy cores and six patients with inadequately stained margins, MR-guided biopsy enabled more accurate delineation of the tumor target volume be means of exclusion of false-positive results in 26{\%} (five of 19 patients), false-negative results in 11{\%} (two of 19 patients) and by guiding extension of tumor boundaries in 16{\%} (three of 19 patients).
Conclusion: The integration of guided biopsy with diagnostic MR imaging is feasible and alters delineation of the tumor target boundary in a substantial proportion of patients considering focal salvage.},
author = {M{\'{e}}nard, Cynthia and Iupati, Douglas and Publicover, Julia and Lee, Jenny and Abed, Jessamine and O'Leary, Gerald and Simeonov, Anna and Foltz, Warren D. and Milosevic, Michael and Catton, Charles and Morton, Gerard and Bristow, Robert and Bayley, Andrew and Atenafu, Eshetu G. and Evans, Andrew J. and Jaffray, David A. and Chung, Peter and Brock, Kristy K. and Haider, Masoom A.},
doi = {10.1148/radiol.14122681},
issn = {15271315},
journal = {Radiology},
number = {1},
pages = {181--191},
title = {{MR-guided prostate biopsy for planning of focal salvage after radiation therapy}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {274},
year = {2015}
}
@article{Mendoza2012,
abstract = {In this paper, we propose a self-assessed adaptive region growing segmentation algorithm. In the context of an experimental virtual-reality surgical planning software platform, our method successfully delineates main tissues relevant for reconstructive surgery, such as fat, muscle, and bone. We rely on a self-tuning approach to deal with a great variety of imaging conditions requiring limited user intervention (one seed). The detection of the optimal parameters is managed internally using a measure of the varying contrast of the growing region, and the stopping criterion is adapted to the noise level in the dataset thanks to the sampling strategy used for the assessment function. Sampling is referred to the statistics of a neighborhood around the seed(s), so that the sampling period becomes greater when images are noisier, resulting in the acquisition of a lower frequency version of the contrast function. Validation is provided for synthetic images, as well as real CT datasets. For the CT test images, validation is referred to manual delineations for 10 cases and to subjective assessment for another 35. High values of sensitivity and specificity, as well as Dice's coefficient and Jaccard's index on one hand, and satisfactory subjective evaluation on the other hand, prove the robustness of our contrast-based measure, even suggesting suitability for calibration of other region-based segmentation algorithms. {\textcopyright} 2010 Springer-Verlag.},
author = {Mendoza, Carlos S. and Acha, Bego{\~{n}}a and Serrano, Carmen and G{\'{o}}mez-C{\'{i}}a, Tom{\'{a}}s},
doi = {10.1007/s00138-010-0274-z},
issn = {09328092},
journal = {Machine Vision and Applications},
keywords = {CT,Region growing,Segmentation,Surgical planning,Virtual reality},
number = {1},
pages = {165--177},
title = {{Fast parameter-free region growing segmentation with application to surgical planning}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {23},
year = {2012}
}
@article{Metz2012,
abstract = {State of the art cardiac computed tomography (CT) enables the acquisition of imaging data of the heart over the entire cardiac cycle at concurrent high spatial and temporal resolution. However, in clinical practice, acquisition is increasingly limited to 3-D images. Estimating the shape of the cardiac structures throughout the entire cardiac cycle from a 3-D image is therefore useful in applications such as the alignment of preoperative computed tomography angiography (CTA) to intra-operative X-ray images for improved guidance in coronary interventions. We hypothesize that the motion of the heart is partially explained by its shape and therefore investigate the use of three regression methods for motion estimation from single-phase shape information. Quantitative evaluation on 150 4-D CTA images showed a small, but statistically significant, increase in the accuracy of the predicted shape sequences when using any of the regression methods, compared to shape-independent motion prediction by application of the mean motion. The best results were achieved using principal component regression resulting in point-to-point errors of 2.3$\backslash$pm 0.5 mm, compared to values of 2.7$\backslash$pm 0.6 mm for shape-independent motion estimation. Finally, we showed that this significant difference withstands small variations in important parameter settings of the landmarking procedure. {\textcopyright} 2012 IEEE.},
author = {Metz, Coert T. and Baka, Nora and Kirisli, Hortense and Schaap, Michiel and Klein, Stefan and Neefjes, Lisan A. and Mollet, Nico R. and Lelieveldt, Boudewijn and {De Bruijne}, Marleen and Niessen, Wiro J. and {Van Walsum}, Theo},
doi = {10.1109/TMI.2012.2190938},
issn = {02780062},
journal = {IEEE Transactions on Medical Imaging},
keywords = {Cardiac,heart,motion prediction,principal component regression (PCR),shape,statistical models},
number = {6},
pages = {1311--1325},
title = {{Regression-based cardiac motion prediction from single-phase CTA}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {31},
year = {2012}
}
@article{Meyer2014,
abstract = {Ediacara fossils often exhibit enigmatic taphonomy that complicates morphological characterization and ecological and phylogenetic interpretation; such is the case with Pteridinium simplex from the late Ediacaran Aar Member in southern Namibia. P. simplex is often preserved as three-dimensional (3D) casts and molds in coarse-grained quartzites, making detailed morphological characterization difficult. In addition, P. simplex is often transported, distorted, and embedded in gutter fills or channel deposits, further obscuring its morphologies. By utilizing microfocus X-ray computed tomography (microCT) techniques, we are able to trace individual specimens and their vanes in order to digitally restore the 3D morphology of this enigmatic fossil. Our analysis shows that P. simplex has a very flexible integument that can be bent, folded, twisted, stretched, and torn, indicating a certain degree of elasticity. In the analyzed specimens, we find no evidence for vane identity change or penetrative growth that were previously used as evidence to support a fully endobenthic lifestyle of P. simplex; instead, evidence is consistent with the traditional interpretation of a semi-endobenthic or epibenthic lifestyle. This interpretation needs to be further tested through microCT analysis of P. simplex specimens preserved in situ rather than transported ones. The elastic integument of P. simplex is inconsistent with a phylogenetic affinity with xenophyophore protists; instead, its physical property is consistent with the presence of collagen, chitin, and cellulose, an inference that would provide constraints on the phylogenetic affinity of P. simplex. {\textcopyright} 2014 Elsevier B.V.},
author = {Meyer, Mike and Elliott, David and Wood, Andrew D. and Polys, Nicholas F. and Colbert, Matthew and Maisano, Jessica A. and Vickers-Rich, Patricia and Hall, Michael and Hoffman, Karl H. and Schneider, Gabi and Xiao, Shuhai},
doi = {10.1016/j.precamres.2014.04.013},
issn = {03019268},
journal = {Precambrian Research},
keywords = {Aar member,Ediacaran,MicroCT,Namibia,Pteridinium,Taphonomy},
pages = {79--87},
title = {{Three-dimensional microCT analysis of the Ediacara fossil Pteridinium simplex sheds new light on its ecology and phylogenetic affinity}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {249},
year = {2014}
}
@article{Meyer2017,
abstract = {Trace fossils are superb lines of evidence for examining the ancient biologic world because they offer an opportunity to infer behavioral ecology of organisms. However, traces can be difficult to parse from their matrix, which leads to the loss of important morphological and behavioral data. This is especially true for the earliest marine animal traces from the Ediacaran Period (635–541 Ma), which are usually small ({\textless}5 mm in diameter) and simple (mostly small horizontal trails and burrows), and are sometimes difficult to be distinguished from co-existing tubular body fossils. There is also evidence that the prevalence of microbial substrates in Ediacaran oceans may have influenced emerging trace makers in non-actualistic ways from a late Phanerozoic perspective (e.g., microbial mats may have facilitated a strong geochemical gradient across the sediment-water interface). Therefore, the discovery of the relatively large traces of Lamonte trevallis from the Ediacaran Shibantan Member of the Denying Formation (∼551–541 Ma) in the Yangtze Gorges area of South China provides a unique opportunity to study early bioturbators. These trace fossils are large enough and have sufficient compositional contrast (relative to the matrix) for in situ analysis via X-ray computed tomography (CT) and microcomputed tomography (microCT). Each analytical method has its own advantages and disadvantages. CT scans can image larger specimens, but cannot adequately resolve small features of interest. MicroCT scans can achieve higher resolution, but can only be used with small samples and may involve more post-processing than CT scans. As demonstrated in this study, X-ray CT and microCT in combination with other 3D imaging techniques and resources have the potential to resolve the 3D morphology of Ediacaran trace fossils. A new Volumetric Bioturbation Intensity (VBI) is also proposed, which quantifies whole rock bioturbation using 3D analysis of subsurface traces. Combined with the ability to examine trace fossils in situ, the VBI can enhance our view of ancient ecologies and life's enduring relationship with sediments.},
author = {Meyer, Mike and Polys, Nick and Yaqoob, Humza and Hinnov, Linda and Xiao, Shuhai},
doi = {10.1016/j.precamres.2017.05.010},
issn = {03019268},
journal = {Precambrian Research},
keywords = {Bioturbation,Ediacaran,Lamonte trevallis,South China,Trace fossil},
pages = {341--350},
title = {{Beyond the stony veil: Reconstructing the Earth's earliest large animal traces via computed tomography X-ray imaging}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {298},
year = {2017}
}
@article{Meyer2013,
abstract = {A demonstrator system for planning neurosurgical procedures was developed based on commercial hardware and software. The system combines an easyto- use environment for surgical planning with highend visualization and the opportunity to analyze data sets for research purposes. The demonstrator system is based on the software AMIRA. Specific algorithms for segmentation, elastic registration, and visualization have been implemented and adapted to the clinical workflow. Modules from AMIRA and the image processing library Insight Segmentation and Registration Toolkit (ITK) can be combined to solve various image processing tasks. Customized modules tailored to specific clinical problems can easily be implemented using the AMIRA application programming interface and a self-developed framework for ITK filters. Visualization is done via autostereoscopic displays, which provide a 3D impression without viewing aids. A Spaceball device allows a comfortable, intuitive way of navigation in the data sets. Via an interface to a neurosurgical navigation system, the demonstrator system can be used intraoperatively. The precision, applicability, and benefit of the demonstrator system for planning of neurosurgical interventions and for neurosurgical research were successfully evaluated by neurosurgeons using phantom and patient data sets. {\textcopyright} 2013 Walter de Gruyter GmbH.},
author = {Meyer, Tobias and Ku{\ss}, Julia and Uhlemann, Falk and Wagner, Stefan and Kirsch, Matthias and Sobottka, Stephan B. and Steinmeier, Ralf and Schackert, Gabriele and Morgenstern, Ute},
doi = {10.1515/bmt-2012-0079},
issn = {00135585},
journal = {Biomedizinische Technik},
keywords = {Autostereoscopy,Diffusion tensor imaging,Interaction,Multimodality phantoms,Visualization},
number = {3},
pages = {281--291},
title = {{Autostereoscopic 3D visualization and image processing system for neurosurgery}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {58},
year = {2013}
}
@article{Meyer2013a,
abstract = {Intraoperative optical imaging of intrinsic signals can improve the localization of functional areas of the cortex. On the basis of a review of the current state of technology, a setup was developed and evaluated. The aim was to implement an easy-to-use and robust imaging setup that can be used in clinical routine with standard hardware equipment (surgical microscope, high-resolution camera, stimulator for peripheral nerve stimulation) and custom-made software for intraoperative and postoperative data analysis. Evaluation of different light sources (halogen, xenon) showed a sufficient temporal behavior of xenon light without using a stabilized power supply. Spatial binning (2 ×?2) of the camera reduces temporal variations in the images by preserving a high spatial resolution. The setup was tested in eight patients. Images were acquired continuously for 9 min with alternating 30-s rest and 30-s stimulation conditions. Intraoperative measurement and visualization of high-resolution two-dimensional activity maps could be achieved in 15 min. The detected functional regions corresponded with anatomical and electrophysiological validation. The integration of optical imaging in clinical routine could successfully be achieved using standard hardware, which improves guidance for the surgeon during interventions near the eloquent areas of the brain. {\textcopyright} 2013 Walter de Gruyter GmbH.},
author = {Meyer, Tobias and Sobottka, Stephan B. and Kirsch, Matthias and Schackert, Gabriele and Steinmeier, Ralf and Koch, Edmund and Morgenstern, Ute},
doi = {10.1515/bmt-2012-0072},
issn = {00135585},
journal = {Biomedizinische Technik},
keywords = {Functional imaging,Intrinsic signals,Somatosensory cortex},
number = {3},
pages = {225--236},
title = {{Intraoperative optical imaging of functional brain areas for improved image-guided surgery}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {58},
year = {2013}
}
@inproceedings{Miller,
abstract = {The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new categorisation of the computer vision problem. We first provide a novel decomposition of computer vision into base components which we term the axioms of vision. These are used to define researcher-level and developer-level access to vision algorithms, in a way which does not require expert knowledge of computer vision. We discuss a new line of thought for computer vision by basing analyses on descriptions of the problem instead of in terms of algorithms. From this an abstraction can be developed to provide a layer above algorithmic details. This is extended to the idea of a formal description language which may be automatically interpreted thus allowing those not familiar with computer vision techniques to utilise sophisticated methods. {\textcopyright} 2011 IEEE.},
author = {Miller, Gregor and Fels, Sidney and Oldridge, Steve},
booktitle = {Proceedings - 2011 Canadian Conference on Computer and Robot Vision, CRV 2011},
doi = {10.1109/CRV.2011.29},
isbn = {9780769543628},
keywords = {Computer Vision,Vision Development,Vision Systems},
pages = {168--174},
title = {{A conceptual structure for computer vision}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80051813078{\&}doi=10.1109{\%}2FCRV.2011.29{\&}partnerID=40{\&}md5=dcf66af3aaedbee7cecd406172b38797},
year = {2011}
}
@article{Mistry2013,
abstract = {Purpose: Current implementations of methods based on Hounsfield units to evaluate regional lung ventilation do not directly incorporate tissue-based mass changes that occur over the respiratory cycle. To overcome this, we developed a 4-dimensional computed tomography (4D-CT)-based technique to evaluate fractional regional ventilation (FRV) that uses an individualized ratio of tidal volume to end-expiratory lung volume for each voxel. We further evaluated the effect of different breathing maneuvers on regional ventilation. The results from this work will help elucidate the relationship between global and regional lung function. Methods and Materials: Eight patients underwent 3 sets of 4D-CT scans during 1 session using free-breathing, audiovisual guidance, and active breathing control. FRV was estimated using a density-based algorithm with mass correction. Internal validation between global and regional ventilation was performed by use of the imaging data collected during the use of active breathing control. The impact of breathing maneuvers on FRV was evaluated comparing the tidal volume from 3 breathing methods. Results: Internal validation through comparison between the global and regional changes in ventilation revealed a strong linear correlation (slope of 1.01, R2 of 0.97) between the measured global lung volume and the regional lung volume calculated by use of the "mass corrected" FRV. A linear relationship was established between the tidal volume measured with the automated breathing control system and FRV based on 4D-CT imaging. Consistently larger breathing volumes were observed when coached breathing techniques were used. Conclusions: The technique presented improves density-based evaluation of lung ventilation and establishes a link between global and regional lung ventilation volumes. Furthermore, the results obtained are comparable with those of other techniques of functional evaluation such as spirometry and hyperpolarized-gas magnetic resonance imaging. These results were demonstrated on retrospective analysis of patient data, and further research using prospective data is under way to validate this technique against established clinical tests. {\textcopyright} 2013 Elsevier Inc.},
author = {Mistry, Nilesh N. and Diwanji, Tejan and Shi, Xiutao and Pokharel, Sabin and Feigenberg, Steven and Scharf, Steven M. and D'Souza, Warren D.},
doi = {10.1016/j.ijrobp.2013.07.032},
issn = {03603016},
journal = {International Journal of Radiation Oncology Biology Physics},
number = {4},
pages = {825--831},
title = {{Evaluation of fractional regional ventilation using 4D-CT and effects of breathing maneuvers on ventilation}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {87},
year = {2013}
}
@article{Mohamed2015,
abstract = {Purpose: To develop a quality assurance (QA) workflow by using a robust, curated, manually segmented anatomic region-of-interest (ROI) library as a benchmark for quantitative assessment of different image registration techniques used for head and neck radiation therapy-simulation computed tomography (CT) with diagnostic CT coregistration. Materials and Methods: Radiation therapy-simulation CT images and diagnostic CT images in 20 patients with head and neck squamous cell carcinoma treated with curative-intent intensity-modulated radiation therapy between August 2011 and May 2012 were retrospectively retrieved with institutional review board approval. Sixty-eight reference anatomic ROIs with gross tumor and nodal targets were then manually contoured on images from each examination. Diagnostic CT images were registered with simulation CT images rigidly and by using four deformable image registration (DIR) algorithms: atlas based, B-spline, demons, and optical flow. The resultant deformed ROIs were compared with manually contoured reference ROIs by using similarity coefficient metrics (ie, Dice similarity coefficient) and surface distance metrics (ie, 95{\%} maximum Hausdorff distance). The nonparametric Steel test with control was used to compare different DIR algorithms with rigid image registration (RIR) by using the post hoc Wilcoxon signed-rank test for stratified metric comparison.. Results: A total of 2720 anatomic and 50 tumor and nodal ROIs were delineated. All DIR algorithms showed improved performance over RIR for anatomic and target ROI conformance, as shown for most comparison metrics (Steel test, P {\textless} .008 after Bonferroni correction). The performance of different algorithms varied substantially with stratification by specific anatomic structures or category and simulation CT section thickness. Conclusion: Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation.},
author = {Mohamed, Abdallah S.R. and Ruangskul, Manee Naad and Awan, Musaddiq J. and Baron, Charles A. and Kalpathy-Cramer, Jayashree and Castillo, Richard and Castillo, Edward and Guerrero, Thomas M. and Kocak-Uzel, Esengul and Yang, Jinzhong and Court, Laurence E. and Kantor, Michael E. and Gunn, G. Brandon and Colen, Rivka R. and Frank, Steven J. and Garden, Adam S. and Rosenthal, David I. and Fuller, Clifton D.},
doi = {10.1148/radiol.14132871},
issn = {15271315},
journal = {Radiology},
number = {3},
pages = {752--763},
title = {{Quality assurance assessment of diagnostic and radiation therapy-simulation CT image registration for head and neck radiation therapy: Anatomic region of interest-based comparison of rigid and deformable algorithms}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {274},
year = {2015}
}
@article{Mok2016,
abstract = {Background: Previously, we proposed interpolated averaged CT (IACT) for improved attenuation correction (AC) in thoracic PET/CT. This study aims to evaluate its feasibility and effectiveness on cardiac PET/CT. Methods: We simulated 18F-FDG distribution using the XCAT phantom with normal and abnormal cardiac uptake. Average activity and attenuation maps represented static PET and respiration average CT (ACT), respectively, while the attenuation maps of end-inspiration/expiration represented 2 helical CTs (HCT). IACT was obtained by averaging the 2 extreme phases and the interpolated phases generated between them. Later, we recruited 4 patients who were scanned 1 hr post 315-428 MBq 18F-FDG injection. Simulated and clinical PET sinograms were reconstructed with AC using (1) HCT, (2) IACT, and (3) ACT. Polar plots and the 17-segment plots were analyzed. Two regions-of-interest were drawn on lesion and background area to obtain the intensity ratio (IR). Results: Polar plots of PETIACT-AC were more similar to PETACT-AC in both simulation and clinical data. Artifacts were observed in various segments in PETHCT-AC. IR differences of HCT as compared to the phantom were up to {\~{}}20{\%}. Conclusions: IACT-AC reduced respiratory artifacts and improved PET/CT matching similarly to ACT-AC. It is a promising low-dose alternate of ACT for cardiac PET/CT.},
author = {Mok, Greta S.P. and Ho, Cobie Y.T. and Yang, Bang Hung and Wu, Tung Hsin},
doi = {10.1007/s12350-015-0140-5},
issn = {15326551},
journal = {Journal of Nuclear Cardiology},
keywords = {PET/CT,attenuation correction,cardiac imaging,respiratory artifacts},
number = {5},
pages = {1072--1079},
title = {{Interpolated average CT for cardiac PET/CT attenuation correction}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {23},
year = {2016}
}
@article{Montin2020,
abstract = {Survival of pediatric patients with brain tumor has increased over the past 20 years, and increasing evidence of iatrogenic toxicities has been reported. In follow-ups, images are acquired at different time points where substantial changes of brain morphology occur, due to childhood physiological development and treatment effects. To address the image registration complexity, we propose two multi-metric approaches (Mplus, Mdot), combining mutual information (MI) and normalized gradient field filter (NGF). The registration performance of the proposed metrics was assessed on a simulated dataset (Brainweb) and compared with those obtained by MI and NGF separately, using mean magnitude and mean angular errors. The most promising metric (Mplus) was then selected and tested on a retrospective dataset comprising 45 pediatric patients who underwent focal radiotherapy for brain cancer. The quality of the realignment was scored by a radiation oncologist using a perceived misalignment metric (PM). All patients but one were assessed as PM ≤ 2 (good alignment), but the remaining one, severely affected by hydrocephalus and pneumocephalus at the first MRI acquisition, scored PM = 5 (unacceptable). These preliminary findings suggest that Mplus might improve the registration accuracy in complex applications such as pediatric oncology, when data are acquired throughout the years of follow-up, and is worth investigating. [Figure not available: see fulltext.].},
author = {Montin, Eros and Belfatto, Antonella and Bologna, Marco and Meroni, Silvia and Cavatorta, Claudia and Pecori, Emilia and Diletto, Barbara and Massimino, Maura and Oprandi, Maria Chiara and Poggi, Geraldina and Arrigoni, Filippo and Peruzzo, Denis and Pignoli, Emanuele and Gandola, Lorenza and Cerveri, Pietro and Mainardi, Luca},
doi = {10.1007/s11517-019-02109-4},
issn = {17410444},
journal = {Medical and Biological Engineering and Computing},
keywords = {Brain MRI,Deformable registration,Image registration,Mutual information,Normalized gradient field,Pediatric brain tumors},
title = {{A multi-metric registration strategy for the alignment of longitudinal brain images in pediatric oncology}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079384742{\&}doi=10.1007{\%}2Fs11517-019-02109-4{\&}partnerID=40{\&}md5=211d8231bb9224f67092a15ccbb09ce3},
year = {2020}
}
@article{Moore2017,
abstract = {This study considers the computationally determined thermal profile of a finely discretized, heterogeneous human body model, simulating a radiofrequency electromagnetic field (RF-EMF) worker wearing protective clothing subject to RF-EMF exposure, and subject to various environmental conditions including high ambient temperature and high humidity, with full thermoregulatory mechanisms in place. How the human body responds in various scenarios was investigated, and the information was used to consider safety limits in current international RF-EMF safety guidelines and standards. It was found that different environmental conditions had minimal impact on the magnitude of the thermal response due to RF-EMF exposure, and that the current safety factor of 10 applied in international RF-EMF safety guidelines and standards for RF-EMF workers is generally conservative, though it is only narrowly so when workers are subjected to the most adverse environmental conditions. Bioelectromagnetics. 38:356–363, 2017. {\textcopyright} 2017 Wiley Periodicals, Inc.},
author = {Moore, Stephen M. and McIntosh, Robert L. and Iskra, Steve and Lajevardipour, Alireza and Wood, Andrew W.},
doi = {10.1002/bem.22048},
issn = {1521186X},
journal = {Bioelectromagnetics},
keywords = {RF-EMF worker,occupational safety,protective clothing,radiofrequency safety standards,temperature rise},
number = {5},
pages = {356--363},
title = {{Effect of adverse environmental conditions and protective clothing on temperature rise in a human body exposed to radiofrequency electromagnetic fields}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016441570{\&}doi=10.1002{\%}2Fbem.22048{\&}partnerID=40{\&}md5=9f2b71c5da61855e410d615f4c57dfd3},
volume = {38},
year = {2017}
}
@article{Mosaliganti2009,
abstract = {In this paper, we utilize the N-point correlation functions (N-pcfs) to construct an appropriate feature space for achieving tissue segmentation in histology-stained microscopic images. The N-pcfs estimate microstructural constituent packing densities and their spatial distribution in a tissue sample. We represent the multi-phase properties estimated by the N-pcfs in a tensor structure. Using a variant of higher-order singular value decomposition (HOSVD) algorithm, we realize a robust classifier that provides a multi-linear description of the tensor feature space. Validated results of the segmentation are presented in a case-study that focuses on understanding the genetic phenotyping differences in mouse placentae. {\textcopyright} 2008 Elsevier B.V. All rights reserved.},
author = {Mosaliganti, Kishore and Janoos, Firdaus and Irfanoglu, Okan and Ridgway, Randall and Machiraju, Raghu and Huang, Kun and Saltz, Joel and Leone, Gustavo and Ostrowski, Michael},
doi = {10.1016/j.media.2008.06.020},
issn = {13618415},
journal = {Medical Image Analysis},
keywords = {Image segmentation,Microstructure,N-point correlation functions,Phenotyping},
number = {1},
pages = {156--166},
title = {{Tensor classification of N-point correlation function features for histology tissue segmentation}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {13},
year = {2009}
}
@article{Mosaliganti2019,
abstract = {Animals make organs of precise size, shape, and symmetry but how developing embryos do this is largely unknown. Here, we combine quantitative imaging, physical theory, and physiological measurement of hydrostatic pressure and fluid transport in zebrafish to study size control of the developing inner ear. We find that fluid accumulation creates hydrostatic pressure in the lumen leading to stress in the epithelium and expansion of the otic vesicle. Pressure, in turn, inhibits fluid transport into the lumen. This negative feedback loop between pressure and transport allows the otic vesicle to change growth rate to control natural or experimentally-induced size variation. Spatiotemporal patterning of contractility modulates pressure-driven strain for regional tissue thinning. Our work connects molecular-driven mechanisms, such as osmotic pressure driven strain and actomyosin tension, to the regulation of tissue morphogenesis via hydraulic feedback to ensure robust control of organ size.},
author = {Mosaliganti, Kishore R. and Swinburne, Ian A. and Chan, Chon U. and Obholzer, Nikolaus D. and Green, Amelia A. and Tanksale, Shreyas and Mahadevan, L. and Megason, Sean G.},
doi = {10.7554/eLife.39596},
issn = {2050084X},
journal = {eLife},
pages = {30},
title = {{Size control of the inner ear via hydraulic feedback}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {8},
year = {2019}
}
@article{Mouches2019,
abstract = {Magnetic resonance angiography (MRA) can capture the variation of cerebral arteries with high spatial resolution. These measurements include valuable information about the morphology, geometry, and density of brain arteries, which may be useful to identify risk factors for cerebrovascular and neurological diseases at an early time point. However, this requires knowledge about the distribution and morphology of vessels in healthy subjects. The statistical arterial brain atlas described in this work is a free and public neuroimaging resource that can be used to identify vascular morphological changes. The atlas was generated based on 544 freely available multi-center MRA and T1-weighted MRI datasets. The arteries were automatically segmented in each MRA dataset and used for vessel radius quantification. The binary segmentation and vessel size information were non-linearly registered to the MNI brain atlas using the T1-weighted MRI datasets to construct atlases of artery occurrence probability, mean artery radius, and artery radius standard deviation. This public neuroimaging resource improves the understanding of the distribution and size of arteries in the healthy human brain.},
author = {Mouches, Pauline and Forkert, Nils D.},
doi = {10.1038/s41597-019-0034-5},
issn = {20524463},
journal = {Scientific data},
number = {1},
pages = {29},
title = {{A statistical atlas of cerebral arteries generated using multi-center MRA datasets from healthy subjects}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {6},
year = {2019}
}
@article{Moudgalya2019,
abstract = {Inner ear disorders such as sensorineural deafness and genetic diseases may one day be treated with local drug delivery to the inner ear. Current pharmacokinetic models have been based on invasive methods to measure drug concentrations, limiting them in spatial resolution, and restricting the research to larger rodents. We developed an intracochlear pharmacokinetic model based on an imaging, learning-prediction (LP) paradigm for learning transport parameters in the murine cochlea. This was achieved using noninvasive micro-computed tomography imaging of the cochlea during in vivo infusion of a contrast agent at the basal end of scala tympani through a cochleostomy. Each scan was registered in 3-D to a cochlear atlas to segment the cochlear regions with high accuracy, enabling concentrations to be extracted along the length of each scala. These spatio-temporal concentration profiles were used to learn a concentration dependent diffusion coefficient, and transport parameters between the major scalae and to clearance. The LP model results are comparable to the current state of the art model, and can simulate concentrations for cases involving different infusion molecules and different drug delivery protocols. Forward simulation results with pulsatile delivery suggest the pharmacokinetic model can be used to optimize drug delivery protocols to reduce total drug delivered and the potential for toxic side effects. While developed in the challenging murine cochlea, the processes are scalable to larger animals and different drug infusion paradigms.},
author = {Moudgalya, Sanketh S. and Wilson, Kevin and Zhu, Xiaoxia and Budzevich, Mikalai M. and Walton, Joseph P. and Cahill, Nathan D. and Frisina, Robert D. and Borkholder, David A.},
doi = {10.1016/j.heares.2019.05.009},
issn = {18785891},
journal = {Hearing Research},
keywords = {3-D image registration,Cochlea,Contrast agent,Inner ear,Micro-computed tomography,Mouse,Optimization,Pharmacokinetics,Segmentation},
pages = {46--59},
title = {{Cochlear pharmacokinetics - Micro-computed tomography and learning-prediction modeling for transport parameter determination}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {380},
year = {2019}
}
@inproceedings{Mueller,
abstract = {Coronary heart disease was the single largest cause of sudden death in Australia in 2002. Computed tomography angiography (CTA) provides high resolution, high contrast images of the thoracic cavity, and as such has emerged as the imaging modality of choice for diagnosing and planning treatment for coronary heart disease. However, radiologists and cardiac surgeons require tools to easily identify possible stenosis (narrowed or constricted coronary vessels) in such CTA datasets. We present a method which allows users to interactively visualise a specific three-dimensional region of interest (ROI). In our example, segmentation methods are applied to isolate the coronary vessels, which in turn are visually enhanced using various perceptual cues. The segmentation is achieved using a combination of thresholding, region-growing, and morphological operations. The perceptual enhancement is realized by fusing direct volume rendered images using weighting factors determined by the segmented regions. The user can allow for the easy dissemination of relevant information by adjusting 'transfer functions' to control the degree of ROI enhancement. This approach requires only roughly segmented regions of interest, and allows for the 3D visualisation of calcifications within vessels. This proposed method has significant potential for helping to facilitate the efficient treatment for coronary heart disease. Furthermore, it can be implemented at interactive framerates on comparatively cheap, desktop computing hardware making it readily accessible. {\textcopyright} 2005 IEEE.},
author = {Mueller, Daniel and Maeder, Anthony and O'Shea, Peter},
booktitle = {Proceedings of the Digital Imaging Computing: Techniques and Applications, DICTA 2005},
doi = {10.1109/DICTA.2005.1578115},
isbn = {0769524672},
pages = {110--117},
title = {{Improved direct volume visualisation of the coronary arteries using fused segmented regions}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33846990428{\&}doi=10.1109{\%}2FDICTA.2005.1578115{\&}partnerID=40{\&}md5=d567baa5b241ec2cbf2f4ffd4a343b46},
volume = {2005},
year = {2005}
}
@article{Mukherjee2016,
abstract = {Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is not susceptible to motion introduced between CT and PET acquisitions. Conclusions: The authors have shown that they can estimate motion for frames with time intervals as short as 5 s using nonattenuation corrected reconstructed FDG PET brain images. Intraframe motion in 60-s frames causes degradation of accuracy to about 2 mm based on the motion type.},
author = {Mukherjee, J. M. and Lindsay, C. and Mukherjee, A. and Olivier, P. and Shao, L. and King, M. A. and Licho, R.},
doi = {10.1118/1.4946814},
issn = {00942405},
journal = {Medical Physics},
keywords = {PET,motion compensation,motion tracking,reconstruction,registration},
number = {5},
pages = {2443--2454},
title = {{Improved frame-based estimation of head motion in PET brain imaging}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {43},
year = {2016}
}
@article{Muschelli2019,
abstract = {Neuroconductor (https://neuroconductor.org) is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: (i) provide a centralized repository of R software dedicated to image analysis, (ii) disseminate software updates quickly, (iii) train a large, diverse community of scientists using detailed tutorials and short courses, (iv) increase software quality via automatic and manual quality controls, and (v) promote reproducibility of image data analysis. Based on the programming language R (https://www.r-project.org/), Neuroconductor starts with 51 inter-operable packages that cover multiple areas of imaging including visualization, data processing and storage, and statistical inference. Neuroconductor accepts new R package submissions, which are subject to a formal review and continuous automated testing. We provide a description of the purpose of Neuroconductor and the user and developer experience.},
author = {Muschelli, John and Gherman, Adrian and Fortin, Jean Philippe and Avants, Brian and Whitcher, Brandon and Clayden, Jonathan D. and Caffo, Brian S. and Crainiceanu, Ciprian M.},
doi = {10.1093/biostatistics/kxx068},
issn = {14684357},
journal = {Biostatistics},
keywords = {Bioinformatics,Image analysis,Statistical modelling},
number = {2},
pages = {218--239},
title = {{Neuroconductor: An R platform for medical imaging analysis}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {20},
year = {2019}
}
@article{Mutsvangwa2015,
abstract = {This paper presents development of statistical shape models based on robust and rigid-groupwise registration followed by pointset nonrigid registration. The main advantages of the pipeline include automation in that the method does not rely on manual landmarks or a regionalization step; there is no bias in the choice of reference during the correspondence steps and the use of the probabilistic principal component analysis framework increases the domain of the shape variability. A comparison between the widely used expectation maximization-iterative closest point algorithm and a recently reported groupwise method on publicly available data (hippocampus) using the well-known criteria of generality, specificity, and compactness is also presented. The proposed method gives similar values but the curves of generality and specificity are superior to those of the other two methods. Finally, the method is applied to the human scapula, which is a known difficult structure, and the human humerus.},
author = {Mutsvangwa, Tinashe and Burdin, Valerie and Schwartz, Cedric and Roux, Christian},
doi = {10.1109/TBME.2014.2368362},
issn = {15582531},
journal = {IEEE Transactions on Biomedical Engineering},
keywords = {humerus,scapula,statistical shape model},
number = {4},
pages = {1098--1107},
title = {{An Automated Statistical Shape Model Developmental Pipeline: Application to the Human Scapula and Humerus}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {62},
year = {2015}
}
@article{Nagatomi2005,
abstract = {Spinal cord injuries (SCI) often lead to severe bladder dysfunctions. Our previous studies have demonstrated that following SCI, rat bladder wall tissue became hypertrophied, significantly more compliant, and changed its mechanical behavior from orthotropic to isotropic. In order to elucidate the link between the tissue microstructure and mechanical properties of the wall, we have developed a novel semi-automated image analysis method to quantify smooth muscle bundle orientation and mass fraction in the bladder wall tissues from normal and 10 day-post-SCI rats. Results of the present study revealed that there were significant (p {\textless} 0.05) increases in smooth muscle area fractions as well as significantly (p {\textless} 0.001) fewer cell nuclei per muscle area in the SCI groups compared to the normal groups. Furthermore, while the normal rat bladders exhibited predominant smooth muscle orientation only in the longitudinal direction, the SCI rat bladders exhibited smooth muscles oriented in both the circumferential and longitudinal directions. These results provide first evidence that bladder smooth muscle cells exhibit hypertrophy rather than hyperplasia and developed a second, orthogonal orientation of smooth muscle bundles following SCI. The results of the present study corroborate our previous mechanical anisotropy data and provide the basis for development of structure-based constitutive models for urinary bladder wall tissue. {\textcopyright} 2005 Biomedical Engineering Society.},
author = {Nagatomi, Jiro and Toosi, K. Khashayar and Grashow, Jonathan S. and Chancellor, Michael B. and Sacks, Michael S.},
doi = {10.1007/s10439-005-5776-x},
issn = {00906964},
journal = {Annals of Biomedical Engineering},
keywords = {Histomorphometery,Image analysis,Mechanical anisotropy,Smooth muscle},
number = {8},
pages = {1078--1089},
title = {{Quantification of bladder smooth muscle orientation in normal and spinal cord injured rats}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-23844453003{\&}doi=10.1007{\%}2Fs10439-005-5776-x{\&}partnerID=40{\&}md5=c94d2c670513b414f8e81daf45d810d7},
volume = {33},
year = {2005}
}
@article{Namias2016,
abstract = {Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed framework has a wide range of applications especially in the presence of adjacent structures of interest or under intra-structure inhomogeneities giving excellent quantitative results.},
author = {Nam{\'{i}}as, Rafael and D'Amato, Juan Pablo and del Fresno, Mariana and V{\'{e}}nere, Marcelo and Pirr{\'{o}}, Nicola and Bellemare, Marc Emmanuel},
doi = {10.1007/s11517-015-1387-3},
issn = {17410444},
journal = {Medical and Biological Engineering and Computing},
keywords = {Collision control,Complex segmentation,Deformable models,Multi-object segmentation,Segmentation framework},
number = {8},
pages = {1181--1192},
title = {{Multi-object segmentation framework using deformable models for medical imaging analysis}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {54},
year = {2016}
}
@article{Nantavithya2020,
abstract = {Introduction: Patterns of local, regional, and distant failure after stereotactic ablative radiotherapy (SABR) for early-stage non-small cell lung cancer (NSCLC) have been widely reported. However, reliable methods for analyzing causes of local failure are lacking. We describe a method for analyzing and reporting patterns of in-field recurrence after SABR, incorporating dosimetric parameters from initial treatment plan as well as geometric information from diagnostic images at recurrence. Material and methods: Diagnostic CT images at recurrence were registered with initial treatment planning images and radiation dose by deformable image registration. Recurrent gross tumor volume (rGTV) and centroid (geometric center of rGTV) were delineated. In-field failure was classified as centroids originating within the original planning target volume. Dose-volume histograms for each rGTV were used to further classify in-field recurrences as central high-dose (dose to 95{\%} of rGTV [rGTVD95{\%}] ≥95{\%} of dose prescribed to PTV) or peripheral high-dose (rGTVD95{\%} {\textless}95{\%} of dose prescribed to PTV). Results: 634 patients received SABR from 2004 to 2014 with 48 local recurrences. 35 of these had evaluable images with 16 in-field recurrences: 9 central high-dose, 6 peripheral high-dose, and 1 had both. Time to and volume of recurrence were not statistically different between central versus peripheral high-dose recurrences. However mean rGTV dose, mean centroid dose, and rGTVD95{\%} were higher for central versus peripheral high-dose recurrences. Conclusion: We report a standardized method for analysis and classification of in-field recurrence after SABR. There were more central as opposed to peripheral high-dose recurrences, suggesting biological rather than technical issues underlying majority of in-field failures.},
author = {Nantavithya, Chonnipa and Gomez, Daniel R. and Chang, Joe Y. and Mohamed, Abdallah S.R. and Fuller, C. David and Li, Heng and Brooks, Eric D. and Gandhi, Saumil J.},
doi = {10.1016/j.radonc.2020.01.002},
issn = {18790887},
journal = {Radiotherapy and Oncology},
keywords = {Early-stage non-small cell lung cancer,In-field recurrence,Stereotactic ablative radiotherapy},
pages = {209--214},
title = {{An improved method for analyzing and reporting patterns of in-field recurrence after stereotactic ablative radiotherapy in early-stage non-small cell lung cancer}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079230198{\&}doi=10.1016{\%}2Fj.radonc.2020.01.002{\&}partnerID=40{\&}md5=fe2e0bf370b46396d4913f6e5289a860},
volume = {145},
year = {2020}
}
@article{Nardelli2015,
abstract = {Background: Computed tomography (CT) helps physicians locate and diagnose pathological conditions. In some conditions, having an airway segmentation method which facilitates reconstruction of the airway from chest CT images can help hugely in the assessment of lung diseases. Many efforts have been made to develop airway segmentation algorithms, but methods are usually not optimized to be reliable across different CT scan parameters. Methods: In this paper, we present a simple and reliable semi-automatic algorithm which can segment tracheal and bronchial anatomy using the open-source 3D Slicer platform. The method is based on a region growing approach where trachea, right and left bronchi are cropped and segmented independently using three different thresholds. The algorithm and its parameters have been optimized to be efficient across different CT scan acquisition parameters. The performance of the proposed method has been evaluated on EXACT'09 cases and local clinical cases as well as on a breathing pig lung phantom using multiple scans and changing parameters. In particular, to investigate multiple scan parameters reconstruction kernel, radiation dose and slice thickness have been considered. Volume, branch count, branch length and leakage presence have been evaluated. A new method for leakage evaluation has been developed and correlation between segmentation metrics and CT acquisition parameters has been considered. Results: All the considered cases have been segmented successfully with good results in terms of leakage presence. Results on clinical data are comparable to other teams' methods, as obtained by evaluation against the EXACT09 challenge, whereas results obtained from the phantom prove the reliability of the method across multiple CT platforms and acquisition parameters. As expected, slice thickness is the parameter affecting the results the most, whereas reconstruction kernel and radiation dose seem not to particularly affect airway segmentation. Conclusion: The system represents the first open-source airway segmentation platform. The quantitative evaluation approach presented represents the first repeatable system evaluation tool for like-for-like comparison between different airway segmentation platforms. Results suggest that the algorithm can be considered stable across multiple CT platforms and acquisition parameters and can be considered as a starting point for the development of a complete airway segmentation algorithm.},
author = {Nardelli, Pietro and Khan, Kashif A. and Corv{\`{o}}, Alberto and Moore, Niamh and Murphy, Mary J. and Twomey, Maria and O'Connor, Owen J. and Kennedy, Marcus P. and Est{\'{e}}par, Ra{\'{u}}l San Jos{\'{e}} and Maher, Michael M. and Cantillon-Murphy, P{\'{a}}draig},
doi = {10.1186/s12938-015-0060-2},
issn = {1475925X},
journal = {BioMedical Engineering Online},
keywords = {3D Slicer,Airway segmentation,Computed tomography (CT),ITK,Image processing,Lung,Region growing},
number = {1},
pages = {24},
title = {{Optimizing parameters of an open-source airway segmentation algorithm using different CT images}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {14},
year = {2015}
}
@article{Narizzano2017,
abstract = {Background: In the evaluation of Stereo-Electroencephalography (SEEG) signals, the physicist's workflow involves several operations, including determining the position of individual electrode contacts in terms of both relationship to grey or white matter and location in specific brain regions. These operations are (i) generally carried out manually by experts with limited computer support, (ii) hugely time consuming, and (iii) often inaccurate, incomplete, and prone to errors. Results: In this paper we present SEEG Assistant, a set of tools integrated in a single 3DSlicer extension, which aims to assist neurosurgeons in the analysis of post-implant structural data and hence aid the neurophysiologist in the interpretation of SEEG data. SEEG Assistant consists of (i) a module to localize the electrode contact positions using imaging data from a thresholded post-implant CT, (ii) a module to determine the most probable cerebral location of the recorded activity, and (iii) a module to compute the Grey Matter Proximity Index, i.e. the distance of each contact from the cerebral cortex, in order to discriminate between white and grey matter location of contacts. Finally, exploiting 3DSlicer capabilities, SEEG Assistant offers a Graphical User Interface that simplifies the interaction between the user and the tools. SEEG Assistant has been tested on 40 patients segmenting 555 electrodes, and it has been used to identify the neuroanatomical loci and to compute the distance to the nearest cerebral cortex for 9626 contacts. We also performed manual segmentation and compared the results between the proposed tool and gold-standard clinical practice. As a result, the use of SEEG Assistant decreases the post implant processing time by more than 2 orders of magnitude, improves the quality of results and decreases, if not eliminates, errors in post implant processing. Conclusions: The SEEG Assistant Framework for the first time supports physicists by providing a set of open-source tools for post-implant processing of SEEG data. Furthermore, SEEG Assistant has been integrated into 3D Slicer, a software platform for the analysis and visualization of medical images, overcoming limitations of command-line tools.},
author = {Narizzano, Massimo and Arnulfo, Gabriele and Ricci, Serena and Toselli, Benedetta and Tisdall, Martin and Canessa, Andrea and Fato, Marco Massimo and Cardinale, Francesco},
doi = {10.1186/s12859-017-1545-8},
issn = {14712105},
journal = {BMC Bioinformatics},
keywords = {Automatic segmentation,Epilepsy,Epileptic zone detections,GMPI,Medical imaging,SEEG},
number = {1},
pages = {13},
title = {{SEEG assistant: A 3DSlicer extension to support epilepsy surgery}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {18},
year = {2017}
}
@inproceedings{Nett,
abstract = {C-arm based cone-beam CT (CBCT) has evolved into a routine clinical imaging modality to provide threedimensional tomographic image guidance before, during, and after an interventional procedure. It is often used to update the clinician to the state of the patient anatomy and interventional tool placement. Due to the repeatedly use of CBCT, the accumulated radiation dose in an interventional procedure has become a concern. There is a strong desire from both patients and health care providers to reduce the radiation exposure required for these exams. The overall objective of this work is to propose and validate a method to significantly reduce the total radiation dose used during a CBCT image guided intervention. The basic concept is that the first cone-beam CT scan acquired at the full dose will be used to constrain the reconstruction of the later CBCT scans acquired at a much lower radiation dose. A recently developed new image reconstruction algorithm, Prior Image Constrained Compressed Sensing (PICCS), was used to reconstruct subsequent CBCT images with lower dose. This application differs from other applications of the PICCS algorithm, such as time-resolved CT or fourdimensional CBCT (4DCBCT), because the patient position may be frequently changed from one CBCT scan to another during the procedure. Thus, an image registration step to account for the change in patient position is indispensable for use of the PICCS image reconstruction algorithm. In this paper, the image registration step is combined with the PICCS algorithm to enable radiation dose reduction in CBCT image guided interventions. Experimental results acquired from a clinical C-arm system using a human cadaver were used to validate the PICCS algorithm based radiation dose reduction scheme. Using the proposed method in this paper, it has been demonstrated that, instead of 300 view angles, this technique requires about 20 cone-beam view angles to reconstruct CBCT angiograms. This signals a radiation dose reduction by a factor of approximately fifteen for subsequent acquisitions.},
author = {Nett, Brian and Tang, Jie and Aagaard-Kienitz, Beverly and Rowley, Howard and Chen, Guang-Hong},
booktitle = {Medical Imaging 2009: Physics of Medical Imaging},
doi = {10.1117/12.813800},
isbn = {9780819475091},
issn = {16057422},
pages = {725803},
title = {{Low radiation dose C-arm cone-beam CT based on prior image constrained compressed sensing (PICCS): including compensation for image volume mismatch between multiple data acquisitions}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-66749095565{\&}doi=10.1117{\%}2F12.813800{\&}partnerID=40{\&}md5=7427199cbd63c3c0e9c00bf6c4c4ff1e},
volume = {7258},
year = {2009}
}
@article{Nketia2017,
abstract = {Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug development. Image analysis methods are needed to extract quantitative information from these vast and complex data sets. The aim of this review is to provide an overview of available image analysis methods for live cell imaging, in particular required preprocessing image segmentation, cell tracking and data visualisation methods. The potential opportunities recent advances in machine learning, especially deep learning, and computer vision provide are being discussed. This review includes overview of the different available software packages and toolkits.},
author = {Nketia, Thomas A. and Sailem, Heba and Rohde, Gustavo and Machiraju, Raghu and Rittscher, Jens},
doi = {10.1016/j.ymeth.2017.02.007},
issn = {10959130},
journal = {Methods},
keywords = {Biological image analysis,Cell segmentation,Cell tracking,Live cell imaging,Machine learning,Quantitative biological imaging},
pages = {65--79},
title = {{Analysis of live cell images: Methods, tools and opportunities}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {115},
year = {2017}
}
@article{Oelschlagel2013,
abstract = {Intraoperative optical imaging (IOI) is a localization method for functional areas of the human brain cortex during neurosurgical procedures. The aim of the current work was to develop of a new analysis technique for the computation of two-dimensional IOI activity maps that is suited especially for use in clinical routine. The new analysis technique includes a stimulation scheme that comprises 30-s rest and 30-s stimulation conditions, in connection with pixelwise spectral power analysis for activity map calculation. A software phantom was used for verification of the implemented algorithms as well as for the comparison with the commonly used relative difference imaging method. Furthermore, the analysis technique was tested using intraoperative measurements on eight patients. The comparison with the relative difference algorithm revealed an averaged improvement of the signal-to-noise ratio between 95{\%} and 130{\%} for activity maps computed from intraoperatively acquired patient datasets. The results show that the new imaging technique improves the activity map quality of IOI especially under difficult intraoperative imaging conditions and is therefore especially suited for use in clinical routine. {\textcopyright} 2013 Walter de Gruyter GmbH.},
author = {Oelschlagel, Martin and Meyer, Tobias and Wahl, Hannes and Sobottka, Stephan B. and Kirsch, Matthias and Schackert, Gabriele and Morgenstern, Ute},
doi = {10.1515/bmt-2012-0077},
issn = {00135585},
journal = {Biomedizinische Technik},
keywords = {Data analysis,Intrinsic signals,Optical imaging,Spectral analysis},
number = {3},
pages = {257--267},
title = {{Evaluation of intraoperative optical imaging analysis methods by phantom and patient measurements}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {58},
year = {2013}
}
@inproceedings{Oliveira,
abstract = {This paper presents a method based on level sets to segment the liver using Computer Tomography (CT) images. Initially, the liver boundary is manually set in one slice as an initial solution, and then the method automatically segments the liver in all other slices, sequentially. In each step of iteration it fits a Gaussian curve to the liver histogram to model the speed image in which the level sets propagates. The parameters of our method were estimated using Genetic Algorithms (GA) and a database of reference segmentations. The method was tested using 20 different exams and five different measures of performance, and the results obtained confirm the potential of the method. The cases in which the method presented a poor performance are also discussed in order to instigate further research.},
author = {Oliveira, D{\'{a}}rio A.B. and Feitosa, Raul Q. and Correia, Mauro M.},
booktitle = {VISAPP 2009 - Proceedings of the 4th International Conference on Computer Vision Theory and Applications},
doi = {10.5220/0001787401540159},
isbn = {9789898111692},
keywords = {Computer tomography,Genetic algorithms,Level sets,Liver segmentation,Medical imaging},
pages = {154--159},
title = {{Liver segmentation using level sets and genetic algorithms}},
type = {Conference Proceedings},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349298510{\&}partnerID=40{\&}md5=921f6aa504ccbbbf03902b5d0fbb632b},
volume = {2},
year = {2009}
}
@article{Oliveira2011,
abstract = {Background: Cancer treatments are complex and involve different actions, which include many times a surgical procedure. Medical imaging provides important information for surgical planning, and it usually demands a proper segmentation, i.e., the identification of meaningful objects, such as organs and lesions. This study proposes a methodology to segment the liver, its vessels and nodules from computer tomography images for surgical planning.Methods: The proposed methodology consists of four steps executed sequentially: segmentation of liver, segmentation of vessels and nodules, identification of hepatic and portal veins, and segmentation of Couinaud anatomical segments. Firstly, the liver is segmented by a method based on a deformable model implemented through level sets, of which parameters are adjusted by using a supervised optimization procedure. Secondly, a mixture model is used to segment nodules and vessels through a region growing process. Then, the identification of hepatic and portal veins is performed using liver anatomical knowledge and a vein tracking algorithm. Finally, the Couinaud anatomical segments are identified according to the anatomical liver model proposed by Couinaud.Results: Experiments were conducted using data and metrics brought from the liver segmentation competition held in the Sliver07 conference. A subset of five exams was used for estimation of segmentation parameter values, while 15 exams were used for evaluation. The method attained a good performance in 17 of the 20 exams, being ranked as the 6thbest semi-automatic method when comparing to the methods described on the Sliver07 website (2008). It attained visual consistent results for nodules and veins segmentation, and we compiled the results, showing the best, worst, and mean results for all dataset.Conclusions: The method for liver segmentation performed well, according to the results of the numerical evaluation implemented, and the segmentation of liver internal structures were consistent with the anatomy of the liver, as confirmed by a specialist. The analysis provided evidences that the method to segment the liver may be applied to segment other organs, especially to those whose distribution of voxel intensities is nearly Gaussian shaped. {\textcopyright} 2011 Oliveira et al; licensee BioMed Central Ltd.},
author = {Oliveira, D{\'{a}}rio A.B. and Feitosa, Raul Q. and Correia, Mauro M.},
doi = {10.1186/1475-925X-10-30},
issn = {1475925X},
journal = {BioMedical Engineering Online},
title = {{Segmentation of liver, its vessels and lesions from CT images for surgical planning}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79954573225{\&}doi=10.1186{\%}2F1475-925X-10-30{\&}partnerID=40{\&}md5=c81b11df842390263ed95985f684c387},
volume = {10},
year = {2011}
}
@article{Ozbolat2016,
abstract = {In order to bioprint living tissue and organ constructs, patient-specific anatomical models need to be acquired; however, these models mainly provide external surface information only. The internal architecture of tissue constructs plays a crucial role as it provides a porous environment for media exchange, vascularization, tissue growth and engraftment. This review presents design requirements for bioprinting and discusses currently available medical imaging techniques used in acquisition of anatomical models including magnetic resonance imaging (MRI) and computed tomography (CT), and compares their strengths and limitations. Then, consideration for design architecture is discussed and various approaches in blueprint modeling of tissue constructs are presented for creation of porous architectures. Next, existing toolpath planning approaches for bioprinting of tissues and organs are presented. Design limitations for bioprinting are discussed and future perspectives are provided to the reader.},
author = {Ozbolat, Ibrahim and Gudapati, Hemanth},
doi = {10.1016/j.bprint.2016.11.001},
issn = {24058866},
journal = {Bioprinting},
keywords = {Blueprint modeling,Design requirements for bioprinting,Medical imaging,Toolpath planning},
pages = {1--14},
title = {{A review on design for bioprinting}},
type = {Journal Article},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016144668{\&}doi=10.1016{\%}2Fj.bprint.2016.11.001{\&}partnerID=40{\&}md5=be8ae863546f5861c3ed0df09aaee711},
volume = {3},
year = {2016}
}
@book{Ozbolat2016a,
author = {Ozbolat, I T},
pages = {1--342},
series = {3D Bioprinting: Fundamentals, Principles and Applications},
title = {{3D Bioprinting: Fundamentals, Principles and Applications}},
type = {Book},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014448877{\&}partnerID=40{\&}md5=e0d277bc12f4ddba45e2cdccfbae6cbc},
year = {2016}
}
@book{Ozbolat2017,
abstract = {To bioprint tissue and organ constructs, patient-specific anatomical models need to be obtained; however, these models mainly provide external surface information only. The internal architecture of tissue constructs plays a crucial role as it provides a porous environment for media exchange, vascularization, tissue growth, and engraftment. This chapter discusses currently available medical imaging techniques used in acquisition of anatomical models, including magnetic resonance imaging, computed tomography, and ultrasound, and compares their strengths and limitations. Then, consideration for design architecture is discussed, and various approaches in blueprint modeling of tissue constructs are presented for creation of porous architectures. Next, existing toolpath planning approaches for bioprinting of tissues and organs are presented. Design limitations for bioprinting are discussed, and future perspectives are provided to the reader.},
address = {London},
author = {Ozbolat, Ibrahim T.},
booktitle = {3D Bioprinting},
doi = {10.1016/b978-0-12-803010-3.00002-0},
isbn = {978-0-12-803030-1; 978-0-12-803010-3},
pages = {13--39},
publisher = {Academic Press Ltd-Elsevier Science Ltd},
series = {3d Bioprinting: Fundamentals, Principles and Applications},
title = {{Design for Bioprinting}},
type = {Book},
url = {{\%}3CGo to},
year = {2017}
}
@article{Park2017,
abstract = {Purpose: We developed an image-guided intervention robot system that can be operated in a magnetic resonance (MR) imaging gantry. The system incorporates a bendable needle intervention robot for breast cancer patients that overcomes the space limitations of the MR gantry. Methods: Most breast coil designs for breast MR imaging have side openings to allow manual localization. However, for many intervention procedures, the patient must be removed from the gantry. A robotic manipulation system with integrated image guidance software was developed. Our robotic manipulator was designed to be slim, so as to fit between the patient's side and the MR gantry wall. Only non-magnetic materials were used, and an electromagnetic shield was employed for cables and circuits. The image guidance software was built using open source libraries. In situ feasibility tests were performed in a 3-T MR system. One target point in the breast phantom was chosen by the clinician for each experiment, and our robot moved the needle close to the target point. Results: Without image-guided feedback control, the needle end could not hit the target point (distance = 5 mm) in the first experiment. Using our robotic system, the needle hits the target lesion of the breast phantom at a distance of 2.3 mm from the same target point using image-guided feedback. The second experiment was performed using other target points, and the distance between the final needle end point and the target point was 0.8 mm. Conclusions: We successfully developed an MR-guided needle intervention robot for breast cancer patients. Further research will allow the expansion of these interventions.},
author = {Park, Samuel Byeongjun and Kim, Jung Gun and Lim, Ki Woong and Yoon, Chae Hyun and Kim, Dong Jun and Kang, Han Sung and Jo, Yung Ho},
doi = {10.1007/s11548-017-1528-2},
issn = {18616429},
journal = {International Journal of Computer Assisted Radiology and Surgery},
keywords = {Bendable needle,Breast cancer,Magnetic resonance imaging,Medical robotics,Needle intervention},
number = {8},
pages = {1319--1331},
title = {{A magnetic resonance image-guided breast needle intervention robot system: overview and design considerations}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {12},
year = {2017}
}
@article{Parsons2017,
author = {Parsons, Stephen and Parker, C. Seth and Seales, W. Brent},
doi = {10.1353/mns.2017.0022},
issn = {23801190},
journal = {Manuscript Studies},
number = {2},
pages = {483--498},
title = {{The St. Chad Gospels: Diachronic manuscript registration and visualization}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {2},
year = {2017}
}
@article{Patel2018,
abstract = {Purpose: To assess variability in corneal ulcer measurements between ophthalmologists and reduce clinician-dependent variability using semiautomated segmentation of the ulcer from photographs. Methods: Three ophthalmologists measured 50 patients' eyes for epithelial defects (EDs) and the stromal infiltrate (SI) size using slit-lamp (SL) calipers. SL photographs were obtained. An algorithm was developed for semiautomatic segmenting of the ED and SI in the photographs. Semiautomatic segmentation was repeated 3 times by different users (2 ophthalmologists and 1 trainee). Clinically significant variability was assessed with intraclass correlation coefficients (ICCs) and the percentage of pairwise measurements differing by ≥0.5 mm. Semiautomatic segmentation measurements were compared with manual delineation of the image by a corneal specialist (gold standard) using Dice similarity coefficients. Results: Ophthalmologists' reliability in measurements by SL calipers had an ICC from 0.84 to 0.88 between examiners. Measurements by semiautomatic segmentation had an ICC from 0.96 to 0.98. SL measures of ulcers by clinical versus semiautomatic segmentation measures differed by ≥0.5 mm in 24{\%} to 38{\%} versus 8{\%} to 28{\%} (ED height); 30{\%} to 52{\%} versus 12{\%} to 34{\%} (ED width); 26{\%} to 38{\%} versus 10{\%} to 32{\%} (SI height); and 38{\%} to 58{\%} versus 14{\%} to 34{\%} (SI width), respectively. Average Dice similarity coefficients between manual and repeated semiautomatic segmentation ranged from 0.83 to 0.86 for the ED and 0.78 to 0.83 for the SI. Conclusions: Variability exists when measuring corneal ulcers, even among ophthalmologists. Photography and computerized methods for quantifying the ulcer size could reduce variability while remaining accurate and impact quantitative measurement endpoints.},
author = {Patel, Tapan P. and Prajna, N. Venkatesh and Farsiu, Sina and Valikodath, Nita G. and Niziol, Leslie M. and Dudeja, Lakshey and Kim, Kyeong Hwan and Woodward, Maria A.},
doi = {10.1097/ICO.0000000000001488},
issn = {15364798},
journal = {Cornea},
keywords = {corneal ulcer,interexaminer variability,random forest segmentation,semiautomated measurement},
number = {3},
pages = {331--339},
pmid = {29256985},
title = {{Novel Image-Based Analysis for Reduction of Clinician-Dependent Variability in Measurement of the Corneal Ulcer Size}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {37},
year = {2018}
}
@article{Patterson2018,
abstract = {Histology-directed imaging mass spectrometry (IMS) is a spatially targeted IMS acquisition method informed by expert annotation that provides rapid molecular characterization of select tissue structures. The expert annotations are usually determined on digital whole slide images of histological stains where the staining preparation is incompatible with optimal IMS preparation, necessitating serial sections: one for annotation, one for IMS. Registration is then used to align staining annotations onto the IMS tissue section. Herein, we report a next-generation histology-directed platform implementing IMS-compatible autofluorescence (AF) microscopy taken prior to any staining or IMS. The platform enables two histology-directed workflows, one that improves the registration process between two separate tissue sections using automated, computational monomodal AF-to-AF microscopy image registration, and a registration-free approach that utilizes AF directly to identify ROIs and acquire IMS on the same section. The registration approach is fully automated and delivers state of the art accuracy in histology-directed workflows for transfer of annotations (-3-10 $\mu$m based on 4 organs from 2 species) while the direct AF approach is registration-free, allowing targeting of the finest structures visible by AF microscopy. We demonstrate the platform in biologically relevant case studies of liver stage malaria and human kidney disease with spatially targeted acquisition of sparsely distributed (composing less than one tenth of 1{\%} of the tissue section area) malaria infected mouse hepatocytes and glomeruli in the human kidney case study.},
author = {Patterson, Nathan Heath and Tuck, Michael and Lewis, Adam and Kaushansky, Alexis and Norris, Jeremy L. and {Van De Plas}, Raf and Caprioli, Richard M.},
doi = {10.1021/acs.analchem.8b02885},
issn = {15206882},
journal = {Analytical Chemistry},
number = {21},
pages = {12404--12413},
title = {{Next Generation Histology-Directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy}},
type = {Journal Article},
url = {{\%}3CGo to},
volume = {90},
year = {2018}
}
@article{Paun2018,
abstract = {During embryogenesis, a mammalian heart develops from a simple tubular shape into a complex 4-chamber organ, going through four distinct phases: early primitive tubular heart, emergence of trabeculations, trabecular remodeling and development of the compact myocardium. In this paper we propose a framework for standardized and subject-independent 3D regional myocardial complexity analysis, applied to analysis of the development of the mouse left ventricle. We propose a standardized subdivision of the myocardium into 3D overlapping regions (in our case 361) and a novel visualization of myocardial complexity, whereupon we: 1) extend the fractal dimension, commonly applied to image slices, to 3D and 2) use volume occupied by the trabeculations in each region together with their surface area, in order to quantify myocardial complexity. The latter provides an intuitive characterization of the complexity, given that compact myocardium will tend to occupy a larger volume with little surface area while high surface area with low volume will correspond to highly trabeculated areas. Using 50 mouse embryo images at 5 different gestational ages (10 subjects per gestational age), we demonstrate how the proposed representation and complexity measures describe the development of LV myocardial complexity. The mouse embryo data was acquired using high resolution episcopic microscopy. The complexity analysis per region was carried out using: 3D fractal dimension, myocardial volume, myocardial surface area and ratio between the two. The analysis of gestational ages was performed on embryos of 14.5, 15.5, 16.5, 17.5 and 18.5 embryonic days, and demonstrated that the regional complexity of the trabeculations increases longitudinally from the base to the apex, with a maximum around the middle. The overall complexity decreases with gestational age, being most complex at 14.5. Circumferentially, at ages 14.5, 15.5 and 16

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