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Shape discrimination in the hippocampus using an MDL model.

Rhodri H Davies1, Carole J Twining, P Daniel Allen

  • 1Howard Florey Institute, University of Melbourne, Australia. rhodri.davies@hfi.unimelb.edu.au

Information Processing in Medical Imaging : Proceedings of the ... Conference
|September 4, 2004
PubMed
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We developed a new method for building 3D statistical shape models automatically. This approach improves accuracy and efficiency, revealing significant shape differences in the hippocampus between schizophrenic and control groups.

Area of Science:

  • Medical image analysis
  • Computational anatomy
  • Statistical shape modeling

Background:

  • Statistical shape models (SSMs) are crucial for analyzing anatomical variations.
  • Existing methods for automated SSM construction face challenges in scalability and accuracy.
  • Hippocampal shape analysis is important for understanding neurological conditions.

Purpose of the Study:

  • To introduce a novel, scalable, and accurate method for automated 3D statistical shape model construction.
  • To apply this new method to model the right hippocampus and compare its performance against existing techniques.
  • To investigate shape differences in the hippocampus between schizophrenic patients and healthy controls.

Main Methods:

  • Developed an optimized approach for 3D SSM construction using minimum description length and surface re-parameterization.

Related Experiment Videos

  • Built a 3D SSM of the right hippocampus from 82 manually segmented 3D MR brain images.
  • Employed linear discriminant analysis to identify shape variations differentiating patient subgroups.

    • Main Results:

    • The new method produced a more specific, general, and compact hippocampal shape model compared to a previously published method.
    • A statistically significant difference in hippocampal shape was detected between schizophrenic and control subgroups using both models.
    • The proposed method demonstrated a more significant detection of shape differences.

    Conclusions:

    • The novel automated approach offers superior performance in building 3D statistical shape models.
    • Significant hippocampal shape alterations are associated with schizophrenia.
    • The developed model effectively visualizes and quantifies these shape variations.