Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters

  • Adrian Dalca
  • Giovanna Danagoulian
  • Ron Kikinis
  • Ehud Schmidt
  • Polina Golland
Conference paper

DOI: 10.1007/978-3-642-23626-6_66

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6893)
Cite this paper as:
Dalca A., Danagoulian G., Kikinis R., Schmidt E., Golland P. (2011) Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters. In: Fichtinger G., Martel A., Peters T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6893. Springer, Berlin, Heidelberg

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.

Keywords

nerve bundles tracking segmentation particle filter 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Adrian Dalca
    • 1
  • Giovanna Danagoulian
    • 2
  • Ron Kikinis
    • 2
    • 3
  • Ehud Schmidt
    • 2
  • Polina Golland
    • 1
  1. 1.MIT Computer Science and Artificial InteligenceCambridgeUSA
  2. 2.Department of RadiologyBrigham and Women’s HospitalBostonUSA
  3. 3.Surgical Planning LaboratoryBrigham and Women’s HospitalBostonUSA

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