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Level set modeling and segmentation of diffusion tensor magnetic resonance imaging brain data

Zhukov, Leonid and Museth, Ken and Breen, David and Barr, Alan H. and Whitaker, Ross (2003) Level set modeling and segmentation of diffusion tensor magnetic resonance imaging brain data. Journal of Electronic Imaging, 12 (1). pp. 125-133. ISSN 1017-9909. https://resolver.caltech.edu/CaltechAUTHORS:20161025-130839144

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Abstract

Segmentation of anatomical regions of the brain is one of the fundamental problems in medical image analysis. It is traditionally solved by iso-surfacing or through the use of active contours/deformable models on a gray-scale magnetic resonance imaging (MRI) data. We develop a technique that uses anisotropic diffusion properties of brain tissue available from diffusion tensor (DT)-MRI to segment brain structures. We develop a computational pipeline starting from raw diffusion tensor data through computation of invariant anisotropy measures to construction of geometric models of the brain structures. This provides an environment for user-controlled 3-D segmentation of DT-MRI datasets. We use a level set approach to remove noise from the data and to produce smooth, geometric models. We apply our technique to DT-MRI data of a human subject and build models of the isotropic and strongly anisotropic regions of the brain. Once geometric models have been constructed they can be combined to study spatial relationships and quantitatively analyzed to produce the volume and surface area of the segmented regions.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1117/1.1527628DOIArticle
http://electronicimaging.spiedigitallibrary.org/article.aspx?articleid=1097925PublisherArticle
Additional Information:© 2003 SPIE and IS&T. Paper MIP-13 received May 1, 2001; revised manuscript received Oct. 1, 2001; accepted for publication Mar. 1, 2002. We would like to thank Dr. J. Michael Tyszka, Dr. Miriam Scadeng, and Dr. David Dubowitz for helping us to identify the 3-D structures extracted from the DT dataset. Dr. Jason Wood developed the Iris Explorer modules used to produce part of the results in the paper. This work was supported by National Science Foundation (NSF) Grants No. ACI-9982273 and No. ASC-89-20219, the National Institute on Drug Abuse, the National Institute of Mental Health, and the NSF, as part of the Human Brain Project, Office of Naval Research Volume Visualization Grant No. N000140110033, and the National Library of Medicine “Insight” Project No. N01-LM-0-3503. The first DT-MRI dataset is courtesy of the University of Utah SCI Institute, the second dataset is courtesy of Dr. Mark Bastin, University of Edinburgh, United Kingdom. Finally, we would like to thank our reviewers for a very detailed review and multiple valuable suggestions.
Funders:
Funding AgencyGrant Number
NSFACI-9982273
NSFASC-89-20219
National Institute on Drug AbuseUNSPECIFIED
National Institute of Mental Health (NIMH)UNSPECIFIED
NSFUNSPECIFIED
Office of Naval Research (ONR)N000140110033
National Library of MedicineN01-LM-0-3503
Issue or Number:1
Record Number:CaltechAUTHORS:20161025-130839144
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20161025-130839144
Official Citation:Leonid Zhukov ; Ken Museth ; David Breen ; Alan H. Barr and Ross Whitaker "Level set modeling and segmentation of diffusion tensor magnetic resonance imaging brain data", J. Electron. Imaging. 12(1), 125-133 (Jan 01, 2003). ; http://dx.doi.org/10.1117/1.1527628
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:71460
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:25 Oct 2016 20:57
Last Modified:03 Oct 2019 16:07

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