Abstract
The frequency of breast cancer cases in women is increasing worldwide. A substantial amount of time is taken for a histopathologist to analyse the tissue slide. There is a need for automated systems to aid the pathologist for the detection of malignancy. Early detection of breast cancer leads to faster treatment and increases the chances of survival. It is crucial for the researchers to design systems that can increase the speed and accuracy of the diagnosis of breast cancer. Histological analysis is a prominent approach in the detection of breast cancer. Histopathology images are complex in nature with heterogeneous background and distorted shaped nucleus on it. With the advancements in image processing techniques, there are various solutions given by researchers for processing histology images. Breast cancer computer aided diagnosis system developers need to have insight knowledge of histology slide preparation and manual study of the slides. This will help them to mimic the histopathologist while designing the system and increase the accuracy and reliability of the system. This paper covers in depth study of breast biopsy, histological slide description, image processing techniques for automated histopathology analysis and breast cancer.
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Kanojia, M.G., Ansari, M.A.M.H., Gandhi, N., Yadav, S.K. (2021). Image Processing Techniques for Breast Cancer Detection: A Review. In: Abraham, A., Siarry, P., Ma, K., Kaklauskas, A. (eds) Intelligent Systems Design and Applications. ISDA 2019. Advances in Intelligent Systems and Computing, vol 1181. Springer, Cham. https://doi.org/10.1007/978-3-030-49342-4_63
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