Mammogram segmentation using region based method with split and merge technique

Abstract

Objectives: Now a days, the major health risk in woman is breast cancer. In order to reduce the death rate, early detection of cancerous region in mammogram images is needed. But finding the lesion part and its spread from the mammogram image is very difficult. To identify the type of cancer, segmentation of lesion region is important. To perform further breast cancer classification, this paper proposes an improved segmentation algorithm using digital mammogram. Method/Analysis: An automated method is used to segment the affected mammogram in a effective manner using split and merging technique based on region based segmentation method by identifying a seed point .The proposed algorithm uses morphological operation to remove the noise digitally and region split and merge technique to remove the background and separate the affected region in the image. Findings: The efficiency of this proposed algorithm is calculated by measuring five different parameters Mean, Variance, standard deviation, entropy, correlation and the output is compared with existing technique and it is observed that proposed method shows better results than previous threshold decomposition method. Improvement: From the segmented output the features are extracted for finding the type of cancer from the mass and Micro calcification region.