BCSD-2024V2

Among women, breast cancer is a prominent cancer type. Like any other type of cancer, the most crucial aspects influencing the prognosis of breast cancer are early identification and detection. With the use of computers, screening based on mammography provides help in the detection process of breast cancer at an initial stage. Many researchers have examined and put forth techniques for computer-aided diagnosis (CADx) of anomalies associated with breast cancer in mammography throughout the previous fifteen years. CADx frameworks are designed to assist radiologists in providing second opinions regarding breast lesion detection. Big and varied datasets are necessary for training the model of machine learning. They increase the accuracy and resilience of the CADx system by teaching it to recognize patterns linked to breast cancer. Researchers may create and test new image processing and machine learning approaches using comprehensive and well-annotated mammography datasets.