Breast Cancer Computer-Aided Detection System based on Simple Statistical Features and SVM Classification

Yahia Osman,Umar Alqasemi

doi:10.14569/ijacsa.2020.0110153

Abstract

Computer-Aided Detection (CADe) systems are becoming very helpful and useful in supporting physicians for early detection of breast cancer. In this paper, a CADe system that is able to detect abnormal clusters in mammographic images will be implemented using different classifiers and features. The CADe system will utilize a Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) as classifiers. Adopting mammographic database from Mammographic Image Analysis Society (MIAS), for training and testing, the performance of the two types of classifiers are compared in terms of sensitivity, specificity, and accuracy. The obtained values for the previous parameters show the efficiency of the CADe system to be used as a secondary screening method in detecting abnormal clusters given the Region of Interest (ROI). The best classifier is found to be SVM showed 96% accuracy, 92% sensitivity and 100% specificity.

Highlights

Breast cancer is a disease occurred when the cells in the female breast grow randomly and out of control
Several previous studies have been published involving Computer-Aided Detection (CADe) system for breast cancer using mammography, contributed in presenting preprocessing algorithms, new features of more statistical significance or more relevant to the morphology of the abnormal images, and classifiers of better performance combined with set of features
Mammographic Image Analysis Society (MIAS) is organized by U.K research groups that are interested in the understanding of mammograms and for image processing and recognition [10]

Summary

INTRODUCTION

Breast cancer is a disease occurred when the cells in the female breast grow randomly and out of control. A female human breast is made up of three main parts: lobules, ducts, and connective tissue. Most breast cancers begin in the ducts or lobules. When breast cancer spreads to other parts of the body, it is said to have metastasized [1]. The survival rates have been increased due to more awareness about the disease from social media and more availability and advancement of healthcare technology especially mammography and other diagnostic imaging techniques [3]. Mammography is commonly used as a diagnostic imaging technique for detecting breast cancer due to its availability, less imaging duration, and lower cost than other methods such as Magnetic. Our CADe system assumes known ROI by radiologist and supposed to aid at least as a secondary diagnosis method to support surgery decision

LITERATURE REVIEW

DATABASE

METHODOLOGY

RESULTS

CONCLUSION AND DISCUSSION