Detection of Cancer Cells in Mammogram Using Seeded Region Growing Method and Genetic Algorithm

Breast cancer is one of the most common causes of cancer death in women. We can reduced mortality rate by using early detection. Early detection is efficiently performed on Digital Mammograms. Sometimes manual reading will not give the improper result. Computer Aided detection techniques have been developed to improve the performance rate. One of them is Mammography. Mammography is the best available technique to detect cancer cell in its earlier stages. Normally radiologists will perform the mammogram readings it is difficult to provide accurate diagnosis due to variety of factors such as benign appearance of lesions, poor quality of image, eye fatigue factor, and deviation in brightness of objects in mammogram. To increased the performance of detecting the malignancy region in mammograms we are using the genetic algorithm and Seeded Region Growing Algorithm. Seeded region growing selected the Seeds automatically depending on calculating the pixel intensity. Clustering is applied along with genetic algorithm with various Stages selection, Crossover and mutation are the genetic operations performed on the clustered image to produce required results.