Mammography Feature Analysis and Mass Detection in Breast Cancer Images
Bhagwati Charan Patel, Ganesh Ram Sinha · 2014
This paper introduces a novel approach for accomplishing mammographic feature analysis through detection of tumor, in terms of their size and shape with experimental work for early breast tumor detection. The objective is to detect the abnormal tumor/tissue inside breast tissues using three stages: Preprocessing, Segmentation and post processing stage. By using preprocessing noise are remove and than segmentation is applied to detect the mass, after that post processing is applied to find out the benign and malignant tissue with the affected area in the cancers breast image. Size of tumor is also detected in these steps. The occurrences of cancer nodules are identified clearly. Compared with an expert observer reading the Mammography, our algorithm achieves 96.5% sensitivity, 89% specificity, 95.6% accuracy value.