| Literature DB >> 22003741 |
Adrian Dalca1, Giovanna Danagoulian, Ron Kikinis, Ehud Schmidt, Polina Golland.
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.Entities:
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Year: 2011 PMID: 22003741 PMCID: PMC3232745 DOI: 10.1007/978-3-642-23626-6_66
Source DB: PubMed Journal: Med Image Comput Comput Assist Interv