Analysis of U-Net and Modified VGG16 Technique for Mitosis Identification in Histopathology Images

One of the most frequently diagnosed cancers in women is breast cancer.  Mitotic cells in breast histopathological images  are a very important biomarker to diagnose breast cancer. Mitotic scores help medical professionals  to grade breast cancer appropriately. The procedure of identifying mitotic cells is quite time-consuming. To speed up and improve the process, automated deep learning methods can be used. The suggested study aims to conduct analysis on the detection of mitotic cells using U-Net and modified VGG16 technique. In this study, pre-processing of the input images is done using stain normalization and enhancement processes. A modified VGG16 classifier is used to classify the segmented results after the altered image has been segmented using U-Net technology. The suggested method's robustness is evaluated using data from the MITOSIS 2012 dataset. The proposed strategy performed better with a precision of 86%,recall of 75% and F1-Score of 80%.