Spinal Crawlers: Deformable Organisms for Spinal Cord Segmentation and Analysis

  • Chris McIntosh
  • Ghassan Hamarneh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)


Spinal cord analysis is an important problem relating to the study of various neurological diseases. We present a novel approach to spinal cord segmentation in magnetic resonance images. Our method uses 3D “deformable organisms” (DefOrg) an artificial life framework for medical image analysis that complements classical deformable models (snakes and deformable meshes) with high-level, anatomically-driven control mechanisms. The DefOrg framework allows us to model the organism’s body as a growing generalized tubular spring-mass system with an adaptive and predominantly elliptical cross section, and to equip them with spinal cord specific sensory modules, behavioral routines and decision making strategies. The result is a new breed of robust DefOrgs, “spinal crawlers”, that crawl along spinal cords in 3D images, accurately segmenting boundaries, and providing sophisticated, clinically-relevant structural analysis. We validate our method through the segmentation of spinal cords in clinical data and provide comparisons to other segmentation techniques.


Spinal Cord Spinal Cord Injury Medial Axis Medical Image Analysis Deformable Mesh 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chris McIntosh
    • 1
  • Ghassan Hamarneh
    • 1
  1. 1.Medical Image Analysis Lab, School of Computing ScienceSimon Fraser UniversityCanada

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