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Jorge Bernal, F. Javier Sanchez, & Fernando Vilariño. (2011). A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance. In Mario João and Hernández J. and S. Vitrià (Ed.), 5th Iberian Conference on Pattern Recognition and Image Analysis (Vol. 6669, pp. 134–143 ). LNCS.
Abstract: This work aims at the segmentation of colonoscopy images into a minimum number of informative regions. Our method performs in a way such, if a polyp is present in the image, it will be exclusively and totally contained in a single region. This result can be used in later stages to classify regions as polyp-containing candidates. The output of the algorithm also defines which regions can be considered as non-informative. The algorithm starts with a high number of initial regions and merges them taking into account the model of polyp appearance obtained from available data. The results show that our segmentations of polyp regions are more accurate than state-of-the-art methods.
Keywords: Colonoscopy, Polyp Detection, Region Merging, Region Segmentation.