A Survey of Computer‐Aided Diagnosis Systems for Breast Cancer Detection
Charu Anant Rajput, Leninisha Shanmugam, K. Parkavi · 2024
Computer-aided diagnosis (CAD) has been the most critical and vital approach concerning the medical domain in recent times. Also, with the trend of telemedicine in place, the reliability and efficiency of CAD systems have become the need of the hour. Dedicated research concerning CAD systems for the detection of breast cancer is being promoted globally. However, given the vast range of imaging modalities and the availability of diverse datasets concerning the aforementioned domain, choosing the most efficient and optimum implementation methodology becomes a challenge. The proposed survey paper, therefore, aims to provide a comprehensive overview of all of the existing imaging modalities and their corresponding datasets. Apart from this, some notable works concerning each modality representing both the machine learning and deep learning domains would also be presented in order to give a head start for the upcoming novel research. The proposed work would shed light on all the possible categories of classifications that can be performed concerning the domain of breast cancer. We finally conclude by pointing out new possible research gaps, thereby opening up avenues for future upcoming research.