Highly Accurate VGG-19 Model Optimized Deep Learning Classifier for Breast Cancer Identification and Sub Types Classification

This study presents a Medical Image Processing Technique to detect the accuracy in Breast Cancer of a Patient by extracting detailed features from medical images. It proposes a breast cancer discernment through the utilization of Deep learning based VGG-19 model. The process begins with input pre-processing, where techniques are applied to enhance image clarity and suppress noise, ensuring that the subsequent stages work with the best possible data. Segmentation is then performed using Cascaded Fuzzy C-Means (FCM) clustering, which effectively segments portions of the image. Feature extraction follows, employing the GLCM method by deriving meaningful features that characterize the texture and structure of the segmented regions. For the final stage of image classification, the Whale algorithm based optimized VGG-19 convolutional neural network (CNN) architecture is utilized. VGG-19's deep network structure improves classification accuracy by learning complex patterns and distinctions between different image classes.