The Scientific Research Committee at the Department of Computer Sciences and Information held a seminar entitled: “Orthogonal moment features for mammographic mass detection”.
The seminar was presented by Dr. Muhammad Wajih and addressed the invisible mammographic signs of breast cancer which can detect these lumps using mammographic imaging.
This research proposed a system that uses properties such as orthogonal mean constants (OMIs) to detect and diagnose these breast masses. The integration of these three methods of extracting averages and presenting them led to the particle swarm optimization optimization (PSO) algorithm to choose the best one, and (SVM) was applied to classify the image properties.
The proposed system was evaluated using 400 different images and compared with other corresponding applications. The research results show better results than the previous methods with a high accuracy of 93%