title: Segmentation of nerve bundles and ganglia in spine MRI using particle filters.
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.
authors: MIT Computer Science and Artificial Inteligence, Cambridge, MA, USA.
authors: Adrian
authors: A
authors: Dalca
authors: Giovanna
authors: G
authors: Danagoulian
authors: Ron
authors: R
authors: Kikinis
authors: Ehud
authors: E
authors: Schmidt
authors: Polina
authors: P
authors: Golland
mesh_terms: D000465:Algorithms; D001331:Automation; D001921:Brain; D045888:Ganglion Cysts / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D016013:Likelihood Functions; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008953:Models, Anatomic; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D013131:Spine / Q000473:pathology*