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Active Contour and Segmentation Models using Geometric PDE’s for Medical Imaging

  • T. F. Chan
  • L. A. Vese
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

This paper is devoted to the analysis and the extraction of information from bio-medical images. The proposed technique is based on object and contour detection, curve evolution and segmentation. We present a particular active contour model for 2D and 3D images, formulated using the level set method, and based on a 2-phase piecewise-constant segmentation. We then show how this model can be generalized to segmentation of images with more than two segments. The techniques used are based on the Mumford-Shah [21] model. By the proposed models, we can extract in addition measurements of the detected objects, such as average intensity, perimeter, area, or volume. Such informations are useful when in particular a time evolution of the subject is known, or when we need to make comparisons between different subjects, for instance between a normal subject and an abnormal one. Finally, all these will give more informations about the dynamic of a disease, or about how the human body growths. We illustrate the efficiency of the proposed models by calculations on two-dimensional and three-dimensional bio-medical images.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • T. F. Chan
    • 1
  • L. A. Vese
    • 1
  1. 1.Department of MathematicsUniversity of California, Los AngelesLos AngelesUSA

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