Comparative Study of Breast Cancer Detection Using Histopathology Images
Shiva Reshma R, Pradeep R, S. Prabhavathy, B.T. Tharanisrisakthi · 2024
Breast cancer continues to be a major health issue, necessitating efficient and accurate diagnostic methods for early detection. Deep learning approaches have recently showed significant potential in improving the accuracy and efficiency of breast cancer detection, notably in histopathology image processing. This review provides a thorough analysis of existing research on deep and machine-learning applications in breast cancer detection, highlighting the diverse diagnostic setups utilized in various studies. Deep learning is particularly promising in the detection of breast cancer because of its ability to provide accurate, automated, and early detection of potential malignancies, ultimately contributing to better patient outcomes and more effective healthcare practices as a result. The paper explores the range of techniques employed, with a specific focus on different classifiers that works on supervised learning.