Design of an Automated Breast Cancer Masses Detection in Mammogram Using Cellular Neural Network (CNN) Algorithm
Sim Choon Ling, Azian Azamimi Abdullah, Wan Khairunizam · Advanced Science Letters · 2013
Breast cancer is known as the most conventional type of diseases significantly affecting women‟s life world widely. Second leading cause of fatalities in women due to cancer is none other than breast cancer. Women lifetime risk in having breast cancer is aged dependent. According to the breast cancer statistic worldwide, for women lived beyond the age of 70 every 1 in 8 will have very high tendency to develop breast cancer. Mammography remains as the prime option of diagnostic tool for detecting the breast lesion specifically for women aged above 40 years old. Mammogram is believed to have play a pivotal role in early detection of the breast cancer due to it able to detect about 75 percent of the all breast cancers up to at least a year before the ill defined mass continue to grow to the size that is noticeable by both the victim and doctor. Furthermore, studies have proven mammogram able to lesser the risk of fatality up to 35 percent for women aged above 50.