A Review of Computer Aided Diagnosis Model Stage for Mammogram Classification Model

Abstract

Many CAD systems have been developed by various authors using machines or deep learning methods. The goal of such systems is to identify the patients with COVID-19 positive. Most of the existing CAD systems are based on standard steps i.e. pre-processing in which the acquired images are enhanced to get the clear images before providing the input to the CAD system. Segmentation is used to detect disease part or the ROI is segmented from the image. There are many methods used for feature extraction like Otsu thresholding that can extract features from image and identify the area to segment. Finally learning Methods are used to classify images into positive or negative category. In this paper the goal be to explore best learning method to train the system for cancer detection.