Improving breast mass detection using histogram of oriented gradients

Abstract

In this paper we present a simple technique that can be employed to filter the output of the computerized mass detection schemes. The sensitivity of computer-aided detection (CAD) systems is high; nevertheless specificity is not due to high false positive (FP) detection rates. Our approach is based on Histogram of Oriented Gradients (HOG) descriptor for filtering the mass and normal tissue regions. After the descriptors are computed, Support Vector Machines (SVM) are applied to classify the identified masses. The devised technique was tested on 1881 regions of interest (ROIs) acquired using a previously proposed CAD system. Extensive simulations are conducted to illustrate the capacity of the HOG descriptor to improve the performances of mass detection systems.