Local energy-based shape histogram feature extraction technique for breast cancer diagnosis

Wajid, Summrina Kanwal; Hussain, Amir

Abstract

This paper proposes a novel local energy-based shape histogram (LESH) as the feature set for recognition of abnormalities in mammograms. It investigates the implication of this technique on mammogram datasets of the Mammographic Image Analysis Society and INbreast. In the evaluation, regions of interest were extracted from the mammograms, their LESH features were calculated, and they were fed to support vector machine (SVM) classifiers. In addition, the impact of selecting a subset of LESH features on classification performance was also observed and benchmarked against a state-of-the-art wavelet based feature extraction method. The proposed method achieved a higher classification accuracy of range 99.00±0.50 as well as an Az value of 0.9900±0.0050 with multiple SVM kernels where linear kernel performs with 100% accuracy for distinguishing between the abnormalities (masses vs. microcalcifications). Hence, the general capability of the proposed method was established, in which it not only distinguishes between malignant and benign cases for any type of abnormality but also among different types of abnormalities. It is therefore concluded that LESH features are an excellent choice for extracting significant clinical information from mammogram images with significant potential for application to 3-D MRI images.

Citation

Wajid, S. K., & Hussain, A. (2015). Local energy-based shape histogram feature extraction technique for breast cancer diagnosis. Expert Systems with Applications, 42(20), 6990-6999. https://doi.org/10.1016/j.eswa.2015.04.057

• Journal Article Type: Article
• Online Publication Date: May 1, 2015
• Publication Date: Nov 15, 2015
• Deposit Date: Sep 27, 2019
• Journal: Expert Systems with Applications
• Print ISSN: 0957-4174
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 42
• Issue: 20
• Pages: 6990-6999
• DOI: https://doi.org/10.1016/j.eswa.2015.04.057
• Keywords: Computer-aided decision support system (CADSS); Local energy-based shape histogram (LESH); Support vector machine (SVM); Local energy model; Receiver operating characteristic (ROC) curve
• Public URL: http://researchrepository.napier.ac.uk/Output/1792937