Kekre's Fast Codebook Generation algorithm for tumor detection in mammography images
Hemant B. Kekre, Tanuja Sarode, Saylee Gharge · 2010
Segmenting a mammographic images into homogeneous texture regions representing disparate tissue types is often a useful preprocessing step in the computer-assisted detection of breast cancer. That is why we proposed new algorithm to detect cancer in mammogram breast cancer images. In this paper we proposed segmentation using vector quantization technique. Here we used Kekre's Fast Codebook Generation algorithm (KFCG) for segmentation of mammographic images. Initially a codebook of size 128 was generated for mammographic images. These code vectors were further clustered in 8 clusters using same KFCG algorithm. Eight segmented images were obtained for each code vector. These 8 images were displayed as a result. This approach does not leads to over segmentation or under segmentation, as is the case for watershed segmentation and entropy segmentation using Gray Level Co-occurrence Matrix. Results of these algorithms are shown for comparison.