Deformable Organisms for Automatic Medical Image Analysis

  • Ghassan Hamarneh
  • Tim McInerney
  • Demetri Terzopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2208)


We introduce a new paradigm for automatic medical image analysis that adopts concepts from the field of Artificial Life. Our approach prescribes deformable organisms, autonomous agents whose objective is the segmentation and analysis of anatomical structures in medical images. A deformable organism is structured as a ‘muscle’-actuated ‘body’ whose behavior is controlled by a ‘brain’ that is capable of making both reactive and deliberate decisions. This intelligent deformable model possesses an ‘awareness’ of the segmentation process, which emerges from a conflux of perceived sensory data, an internal mental state, memorized knowledge, and a cognitive plan. We develop a class of deformable organisms using a medial representation of body morphology that facilitates a variety of controlled local deformations at multiple spatial scales. Specifically, we demonstrate a deformable ‘worm‘ organism that can overcome noise, incomplete edges, considerable anatomical variation, and occlusion in order to segment and label the corpus callosum in 2D mid-sagittal MR images of the brain.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Ghassan Hamarneh
    • 1
    • 2
  • Tim McInerney
    • 3
    • 2
  • Demetri Terzopoulos
    • 4
    • 2
  1. 1.Dept. of Signals and SystemsChalmers University of TechnologyGöteborgSweden
  2. 2.Dept. of Computer ScienceUniversity of TorontoTorontoCanada
  3. 3.School of Computer ScienceRyerson UniversityTorontoCanada
  4. 4.Courant InstituteNew York UniversityNew YorkUSA

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