NDLI: Impact of Markov Random Field optimizer on MRI-based tissue segmentation in the aging brain

Content Provider	IEEE Xplore Digital Library
Author	Schwarz, C.G. Tsui, A. Fletcher, E. Singh, B. DeCarli, C. Carmichael, O.
Copyright Year	2011
Description	Author affiliation: Neurology Department, University of California, Davis, CA 95616 (Fletcher, E.; Singh, B.; DeCarli, C.) \|\| Computer Science Department, University of California, Davis, CA 95616 (Schwarz, C.G.; Tsui, A.; Carmichael, O.)
Abstract	Automatically segmenting brain magnetic resonance images into grey matter, white matter, and cerebrospinal fluid compartments is a fundamentally important neuroimaging problem whose difficulty is heightened in the presence of aging and neurodegenerative disease. Current methods overlap greatly in terms of identifiable algorithmic components, and the impact of specific components on performance is generally unclear in important real-world scenarios involving serial scanning, multiple scanners, and neurodegenerative disease. Therefore we evaluated the impact that one such component, the Markov Random Field (MRF) optimizer that encourages spatially-smooth tissue labelings, has on brain tissue segmentation performance. Two challenging elderly data sets were used to test segmentation consistency across scanners and biological plausibility of tissue change estimates; and a simulated young brain data set was used to test accuracy against ground truth. Belief propagation (BP) and graph cuts (GC), used as the MRF optimizer component of a standardized segmentation system, provide high segmentation performance on aggregate that is competitive with end-to-end systems provided by SPM and FSL (FAST) as well as the more traditional MRF optimizer iterated conditional modes (ICM). However, the relative performance of each method varied strongly by performance criterion and differed between young and old brains. The findings emphasize the unique difficulties involved in segmenting the aging brain, and suggest that optimal algorithm components may depend in part on performance criteria.
Starting Page	7812
Ending Page	7815
File Size	789561
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6091925
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Aging Magnetic resonance imaging Brain models Labeling
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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