Proposing a Framework to Analyze Breast Cancer in Mammogram Images Using Global Thresholding, Gray Level Co‐Occurrence Matrix, and Convolutional Neural Network (CNN)
Tanishka Dixit, Namrata Singh · 2022
Based on the review and survey I will get a way out to analyze breast cancer in a more precise manner at the initial stage itself by using mammogram images. Initially, pre-processing methods will be applied to align and remove labels and noise from an image. Further, we will be proceeding with segmentation methods where we will be finding the Region of Interest (ROI) and pectoral muscle removal using Global Thresholding and will apply an Artificial Neural Network (ANN). Once this is done, then morphological operations and feature extraction using GLCM will help us in getting more into the details of mammogram images. After this, I will use one of the classification methods, i.e., Convolutional Neural Network (CNN), which will help in obtaining the output with either benign or malignant tissues that will help in taking out a preventive step to cure breast cancer within the human body.