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

Authors:
Adrian Dalca;Giovanna Danagoulian;Ron Kikinis;Ehud Schmidt;Polina Golland
Affiliations:
MIT Computer Science and Artificial Inteligence, Cambridge, MA;Department of Radiology, Brigham and Women's Hospital, Boston, MA;Department of Radiology andSurgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA;Department of Radiology, Brigham and Women's Hospital, Boston, MA;MIT Computer Science and Artificial Inteligence, Cambridge, MA
Venue:
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Year:
2011

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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.