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Automatic segmentation of bladder and prostate using coupled 3D deformable models.

María Jimena Costa1, Hervé Delingette, Sébastien Novellas

  • 1Jimena.Costa@sophia.inria.fr

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|December 7, 2007
PubMed
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We developed an automated method for segmenting the prostate and bladder in CT scans. This approach accurately localizes and delineates these lower abdomen structures, showing promising results in patient data.

Area of Science:

  • Medical Imaging
  • Radiology
  • Computational Anatomy

Background:

  • Accurate segmentation of pelvic organs is crucial for radiation therapy planning and diagnosis.
  • Existing methods often struggle with anatomical variability and image artifacts, particularly in CT scans.
  • Joint segmentation of the prostate and bladder presents unique challenges due to their proximity and potential for shape variation.

Purpose of the Study:

  • To introduce a fully automatic method for coupled 3D localization and segmentation of the prostate and bladder.
  • To address challenges posed by high shape variation and intensity inhomogeneities in lower abdomen CT scans.
  • To develop an adaptive non-overlapping constraint for improved joint segmentation accuracy.

Main Methods:

  • A novel approach combining a flexible bladder segmentation with a statistical shape prior for the prostate.

Related Experiment Videos

  • Implementation of an adaptive non-overlapping constraint to arbitrate structure evolution based on image data.
  • Testing on a database of 16 volumetric CT scans of the lower abdomen.

    • Main Results:

    • The method demonstrated successful coupled 3D localization and segmentation of the prostate and bladder.
    • The flexible approach effectively handled bladder shape variations and intensity inhomogeneities.
    • The adaptive constraint improved the arbitration of evolving structures at their common boundary.
    • Validation included assessment of inter-expert variability, yielding promising results.

    Conclusions:

    • The proposed fully automatic method offers a robust solution for joint prostate and bladder segmentation in CT scans.
    • The technique shows potential for improving accuracy and efficiency in pelvic imaging analysis.
    • Further validation and application in clinical settings are warranted.