ROI segmentation using Local Binary Image
Shubhi Sharma, Pritee Khanna · 2013
Segmentation of ROI is an important and challenging task in the development of CAD system for the detection of breast cancer. This work proposes a Local Binary Image (LBI) to segment the ROI from the mammogram patches. The key idea is to use textural properties of mammogram patches for representing salient micro-patterns of the masses and preserving the spatial information at the same time. Corresponding to the patch, LBI is the binary image where the value 1 represents the presence of texture in the patch. Using LBI the threshold value is identified which is used to extract the mask image. Once the mask image is generated boundary is plotted to trace suspicious area in the patch. The efficiency of the proposed method is tested on a dataset of 819 suspicious patches from the IRMA reference database. The experimental results achieved that the proposed LBI method has successfully attained the value 0.934 for Quality measure.