Segmentation of nerve bundles and ganglia in spine MRI using particle filters

Segmentation of nerve bundles and ganglia in spine MRI using particle filters

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14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III

Bibliographic Details
Main Authors: Dalca, Adrian Vasile (Contributor), Danagoulian, Giovanna (Author), Kikinis, Ron (Author), Schmidt, Ehud (Author), Golland, Polina (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Springer Berlin/Heidelberg, 2012-09-27T21:42:46Z.
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Online Access:Get fulltext
LEADER 02018 am a22002773u 4500
001 73456
042 |a dc 
100 1 0 |a Dalca, Adrian Vasile  |e author 
100 1 0 |a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science  |e contributor 
100 1 0 |a Dalca, Adrian Vasile  |e contributor 
100 1 0 |a Golland, Polina  |e contributor 
700 1 0 |a Danagoulian, Giovanna  |e author 
700 1 0 |a Kikinis, Ron  |e author 
700 1 0 |a Schmidt, Ehud  |e author 
700 1 0 |a Golland, Polina  |e author 
245 0 0 |a Segmentation of nerve bundles and ganglia in spine MRI using particle filters 
260 |b Springer Berlin/Heidelberg,   |c 2012-09-27T21:42:46Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/73456 
520 |a 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III 
520 |a Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation. 
520 |a National Institutes of Health (U.S.) (NAMIC award U54-EB005149) 
520 |a National Science Foundation (U.S.) (CAREER grant 0642971) 
546 |a en_US 
655 7 |a Article 
773 |t Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011 

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