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Automatically segmenting lesion area in breast ultrasound (BUS) images is achallenging one due to its noise, speckle and artifacts. Edge-map of BUS imagesalso does not help because in most cases the edge-map gives no informationwhatsoever. Almost all segmentation technique takes the edge-map of the imageas its first step, though there are a few algorithms that try to avoidedge-maps as well. Improving the edge-map of breast ultrasound imagestheoretically improves the chances of automatic segmentation to be moreprecise. In this paper, we propose a semi-automatic technique of histogramsplitting using two pointers. Here the user only has to select two initiallyguessed points denoting a circle on the region of interest (ROI). The methodwill automatically study the internal histogram and split it using twopointers. The output BUS image has improved edge-map and ultimately thesegmentation on it is better compared to regular segmentation using samealgorithm and same initialization. Also, we further processed the edge-map tohave less edge-pixels to area ratio, improving the homogeneity and the chancesof easy segmentation in the future.

Improving Segmentation of Breast Ultrasound Images: Semi Automatic Two Pointers Histogram Splitting Technique