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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 imugvs recorded in a controlled environment. The second set includes laparoscopic images recorded during three disk removal surgeries performed laparoscopically at Sainte-Justine Hospital.

Segmentation of Laparoscopic Images for Computer Assisted Surgery