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Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin
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A density distance augmented Chan-Vese active contour for CT bone segmentation.

Phan T H Truc1, Sungyoung Lee, Tae-Seong Kim

  • 1Department of Computer Engineering, Kyung Hee University, Rep. of Korea, 446-701.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 24, 2009
PubMed
Summary

This study enhances bone segmentation in CT scans for orthopedic surgery. By adding a Bhattacharyya term to the Chan-Vese active contour model, it improves accuracy for inhomogeneous bone structures.

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Area of Science:

  • Medical Imaging
  • Computer-Assisted Surgery
  • Image Segmentation

Background:

  • Accurate bone segmentation from Computed Tomography (CT) images is crucial for computer-assisted orthopedic surgery.
  • Active contour (AC) models, particularly the Chan-Vese (CV) model, are widely used but struggle with highly inhomogeneous bone structures.
  • The inherent limitation of the CV model is its minimization of intra-object intensity differences, hindering segmentation of complex bone tissues.

Purpose of the Study:

  • To propose an improved active contour model for robust bone segmentation in CT images.
  • To address the limitations of the standard Chan-Vese model in segmenting inhomogeneous bone regions.
  • To enhance the accuracy of bone segmentation for applications in computer-assisted orthopedic surgery.

Main Methods:

  • Incorporation of a Bhattacharyya term into the Chan-Vese active contour functional.
  • The Bhattacharyya term aims to maximize the separability between the probability density functions of the bone (object) and background.
  • Validation using both synthetic and real-world CT image datasets.

Main Results:

  • The proposed modified Chan-Vese model demonstrates improved performance in segmenting bone structures with high inhomogeneity.
  • Preliminary experiments indicate that the Bhattacharyya term effectively enhances the model's ability to distinguish bone from surrounding tissues.
  • The enhanced model overcomes the limitations of the standard CV AC model in challenging segmentation scenarios.

Conclusions:

  • The integration of a Bhattacharyya term offers a promising approach to improve active contour-based bone segmentation in CT imaging.
  • This enhanced model provides a more robust solution for segmenting inhomogeneous bone, advancing computer-assisted orthopedic surgery applications.
  • Further research and validation are warranted to fully explore the clinical utility of this improved segmentation technique.