Title:
Brain MRI T₁-Map and T₁-weighted Image Segmentation in a Variational Framework
Brain MRI T₁-Map and T₁-weighted Image Segmentation in a Variational Framework
dc.contributor.author | Cheng, Ping-Feng | |
dc.contributor.author | Steen, R.Grant | |
dc.contributor.author | Yezzi, Anthony | |
dc.contributor.author | Krim, Hamid | |
dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
dc.date.accessioned | 2013-09-16T19:59:24Z | |
dc.date.available | 2013-09-16T19:59:24Z | |
dc.date.issued | 2009-06 | |
dc.description | © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.description | Presented at the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), 19-24 April 2009, Taipei, Taiwan. | en_US |
dc.description | DOI: 101109/ICASSP.2009.4959609 | en_US |
dc.description.abstract | In this paper we propose a constrained version of Mumford- Shah’s[1] segmentationwith an information-theoretic point of view[2] in order to devise a systematic procedure to segment brain MRI data for two modalities of parametric T₁-Map and T₁-weighted images in both 2-D and 3-D settings. The incorporation of a tuning weight in particular adds a probabilistic flavor to our segmentation method, and makes the three-tissue segmentation possible. Our method uses region based active contours which have proven to be robust. The method is validated by two real objects which were used to generate T₁- Maps and also by two simulated brains of T₁-weighted data from the BrainWeb[3] public database. | en_US |
dc.identifier.citation | Chen, P.F.; Steen, R.G.; Yezzi, A.; & Krim, H. (2009). “Brain MRI T₁-Map and T₁-Weighted Image Segmentation in a Variational Framework.” Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), 19-24 April 2009, pp.417-420. | en_US |
dc.identifier.doi | 10.1109/ICASSP.2009.4959609 | |
dc.identifier.isbn | 978-1-4244-2353-8 | |
dc.identifier.issn | 1520-6149 | |
dc.identifier.uri | http://hdl.handle.net/1853/48951 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.publisher.original | Institute of Electrical and Electronics Engineers | |
dc.subject | Active contour | en_US |
dc.subject | Mumford-Shah | en_US |
dc.subject | Region-based active contour | en_US |
dc.subject | T₁-Map | en_US |
dc.subject | T₁-weighted image | en_US |
dc.title | Brain MRI T₁-Map and T₁-weighted Image Segmentation in a Variational Framework | en_US |
dc.type | Text | |
dc.type.genre | Proceedings | |
dspace.entity.type | Publication | |
local.contributor.author | Yezzi, Anthony | |
local.contributor.corporatename | School of Electrical and Computer Engineering | |
local.contributor.corporatename | College of Engineering | |
relation.isAuthorOfPublication | 53ee63a2-04fd-454f-b094-02a4601962d8 | |
relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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