A fast geodesic active contour model for medical images segmentation using prior analysis

Sharif M.S. Al Sharif, Mohamed Deriche, Nabil Maalej

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The deformable Geodesic Active Contour (GAC) method is one of the most important techniques used in object boundaries detection in images. In this work, we modify the automatic GAC technique by incorporating priori information extracted from the region of interest. We introduce a new stopping function to speed up convergence and improve accuracy. The proposed technique was applied to both synthetic and real medical images. We show an improvement in speed of more than 40% together with an excellent accuracy compared to the traditional GAC model.

Original languageBritish English
Title of host publication2010 2nd International Conference on Image Processing Theory, Tools and Applications, IPTA 2010
Pages300-305
Number of pages6
DOIs
StatePublished - 2010
Event2010 2nd International Conference on Image Processing Theory, Tools and Applications, IPTA 2010 - Paris, France
Duration: 7 Jul 201010 Jul 2010

Publication series

Name2010 2nd International Conference on Image Processing Theory, Tools and Applications, IPTA 2010

Conference

Conference2010 2nd International Conference on Image Processing Theory, Tools and Applications, IPTA 2010
Country/TerritoryFrance
CityParis
Period7/07/1010/07/10

Keywords

  • Boundary detection
  • Deformable models
  • Geometric Active Contour GAC
  • Medical image segmentation
  • Prior information
  • Snake

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