A Review on Breast Cancer Detection for Digital Mammograms

Breast cancer is the second most leading cause of death globally. The mammography technique is considered to be an efficient screening tool for early breast tumor detection. However, it is a challenging task for expert radiologists to interpretation and identification of breast lesions. So, Computer-Aided Diagnosis (CAD) serves as a second opinion to assist radiologists for accurately detecting and for classification of breast cancer in mammograms. This review examines the use of computer-aided diagnosis (CAD) in the diagnosis of breast tumors on mammograms. Numerous studies have demonstrated the potential of CAD to enhance the accuracy of breast cancer detection, particularly in cases where the mammogram is difficult to interpret or the lesion is subtle. CAD systems have been shown to increase sensitivity and reduce false-positive rates, potentially leading to earlier detection and improved outcomes for patients. However, there exist some limitations for the effectiveness of CAD, particularly in certain patient populations, and the implementation of CAD can be costly. Overall, the evidence suggests that CAD can be a valuable tool for improving the accuracy of breast cancer diagnosis on mammograms and should be considered as a valuable adjunct to traditional mammography screening. An in-depth investigation is required to further comprehend the possible advantages and restrictions of CAD in particular patient populations.