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Experimental study demonstrates tumor demarcation in breast mammograms using vector quantization, suggesting improved boundary identification without over-segmentation.
The ability to improve diagnostic information from medical images can be enhanced by designing computer processing algorithms 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 Linde Buzo and Gray (LBG)for segmentation of mammographic images on probability image. Initially probability of input image is calculated and displayed as a result. In second step a codebook of size 128 was generated for probability image. These code vectors were further reclustered in 8 clusters using same LBG algorithm. These 8 images were displayed as a result. This approach does not leads to over segmentation or under segmentation. For the comparison purpose we displayed results of GLCM and watershed segmentation along with this method.
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Kekre et al. (2010) studied this question.
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