Segmentation of nerve bundles and ganglia in spine MRI using particle filters
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Golland_Segmentation of nerve.pdf
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Author(s)
Dalca, Adrian Vasile
Danagoulian, Giovanna
Kikinis, Ron
Schmidt, Ehud
Golland, Polina
Date Issued
September 2011
Journal
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011
Publisher
Springer Berlin/Heidelberg
Citation
Dalca, Adrian et al. “Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters.” Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. Ed. Gabor Fichtinger, Anne Martel, & Terry Peters. LNCS Vol. 6893. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. 537-545.
Version
Author's final manuscript
Abstract
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.
Description
14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1007/978-3-642-23626-6_66
