Concepedia

Abstract

In this paper, we propose novel feature extraction techniques which can provide a high accuracy rate of mass classification in the computer-aided lesion diagnosis of breast tumor. Totally 290 features were extracted using the newly developed border irregularity feature extractor as well as multiple sonographic features based on the breast imaging-reporting and data system (BI-RADS) lexicons. To demonstrate the performance of the proposed features, 4,107 ultrasound images containing 2,508 malignant cases were used. The clinical results demonstrate that the proposed feature combination can be an integral part of ultrasound CAD systems to help accurately distinguish benign from malignant tumors.