Approach for Segmentation of Micro-calcification in Mammographic Images - Chaudhari, Pooja; PB, Bhalerao (International Journal of Computer Sciences and Engineering, 2019)
Ductal Carcinoma (Breast Cancer) is still the most common type of cancer throughout the world and a frequent cause of cancer death among women. Mammography is the most effective and reliable method for accurate detection of breast cancer in recent years. Micro-calcification (MC) is the tiny specks of calcium which appears in the form of clusters in breast tissue. So the detection of MC cluster in breast tissue plays an important role in enhancing the breast cancer diagnosis. In this report, a knowledge-based approach for the automatic detection and segmentation of micro-calcifications in mammographic images is presented. Segmentation is done by using Adaptive Histogram Equalization (AHE) and by calculating range block and domain block of the image. To validate the efficacy of the suggested scheme, simulation has been carried out using Mammography Image Analysis Society (MIAS) database.