Statistical Measures Performance for Preprocessing and Locate ROI Using Segmentation in Mammograms

Breast cancer is a cancer that develops from breast tissue and it is considered one of the deadly
diseases for women. X-ray mammography is the most successful method for the early phase
detection of breast diseases. Micro-calcifications in mammogram have been targeted as earliest
symptom of breast cancer and their detection is very important to improve its prediction. For micro
calcifications, the interpretation of their presence is very tricky because they are very small, typically in
the range of 0.1 mm- 1.0 mm and average is about 0.3 mm. Micro-calcification is a tiny bit, which may
not be clearly visible because of low contrast in the mammogram image. To and locate the region of
interest using segmentation technique. This paper presents statistical measures of different
preprocessing to lighten the low contrast images and selecting filter for accurate detection of
microcalicifications with proper segmentation technique.