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Stephen R. Aylward
Researcher at Kitware
Publications - 66
Citations - 9724
Stephen R. Aylward is an academic researcher from Kitware. The author has contributed to research in topics: Digital image processing & Software. The author has an hindex of 34, co-authored 63 publications receiving 7833 citations. Previous affiliations of Stephen R. Aylward include University of North Carolina at Chapel Hill.
Papers
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Journal ArticleDOI
3D Slicer as an image computing platform for the Quantitative Imaging Network.
Andriy Fedorov,Reinhard Beichel,Jayashree Kalpathy-Cramer,Julien Finet,Jean-Christophe Fillion-Robin,Sonia Pujol,Christian Bauer,Dominique Jennings,Fiona M. Fennessy,Milan Sonka,John M. Buatti,Stephen R. Aylward,James V. Miller,Steve Pieper,Ron Kikinis +14 more
TL;DR: An overview of 3D Slicer is presented as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications and the utility of the platform in the scope of QIN is illustrated.
Journal ArticleDOI
Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction
TL;DR: It is shown that dynamic-scale ridge traversal is insensitive to its initial parameter settings, operates with little additional computational overhead, tracks centerlines with subvoxel accuracy, passes branch points, and handles significant image noise.
Proceedings ArticleDOI
Engineering and algorithm design for an image processing Api: a technical report on ITK--the Insight Toolkit.
Terry S. Yoo,Michael J Ackerman,William E. Lorensen,William J. Schroeder,Vikram Chalana,Stephen R. Aylward,Dimitris N. Metaxas,Ross T. Whitaker +7 more
TL;DR: The detailed planning and execution of the Insight Toolkit (ITK), an application programmers interface (API) for the segmentation and registration of medical image data, is presented.
Journal ArticleDOI
Measuring tortuosity of the intracerebral vasculature from MRA images
TL;DR: This report provides the first 3-D tortuosity analysis of clusters of vessels within the normally tortuous intracerebral circulation and describes a new metric that incorporates counts of minima of total curvature that appears to be the most effective in detecting several types of abnormalities.
Journal ArticleDOI
Vessel tortuosity and brain tumor malignancy: a blinded study.
Elizabeth Bullitt,Donglin Zeng,Guido Gerig,Stephen R. Aylward,Sarang Joshi,J. Keith Smith,Weili Lin,Matthew G. Ewend +7 more
TL;DR: Quantitative, statistical measures of vessel shape offer a new approach to the diagnosis and staging of disease and initial results are promising.