Segmentation of Laparoscopic Images for Computer Assisted Surgery

  • Jonathan Boisvert
  • Farida Cheriet
  • Guy Grimard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)


This paper presents a learning-based approach to the problem of segmentation of laparoscopic images. The first step of the proposed method is to preprocess input images with a homomorphic filter. An initial segmentation map is then computed using a region growing based image segmentation algorithm. The obtained regions are finally classified using a support vector machine (SVM) to produce the final segmentation. The preliminary results computed on two image sets were promising. The first set includes laparoscopic images recorded in a controlled environment. The second set includes laparoscopic images recorded during three disk removal surgeries performed laparoscopically at Sainte-Justine Hospital.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jonathan Boisvert
    • 1
  • Farida Cheriet
    • 1
  • Guy Grimard
    • 2
  1. 1.École Polytechnique de MontréalMontréalCanada
  2. 2.Hôpital Sainte-JustineMontréalCanada

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