Eur. Phys. J. Plus (2018) 133: 455
https://doi.org/10.1140/epjp/i2018-12294-4

Regular Article

Deviation analysis for texture segmentation of breast lesions in mammographic images

¹ Department of Computer Science, COMSATS University Islamabad, Wah Campus, Pakistan
² Department of Mathematics, COMSATS University Islamabad, Wah Campus, Pakistan

^* e-mail: nazeer@hanyang.ac.kr

Received: 25 August 2017
Accepted: 29 August 2018
Published online: 6 November 2018

Abstract

The performance of segmentation methods of breast lesions is often achieved as a vigorous initiative in the automated diagnosis system using color features and mathematical morphology. However, the existing segmentation methods cannot segment the breast mass with high accuracy, particularly the mammogram images that contain the diverse textures. We propose a novel breast mass segmentation technique based on the combination of color space and intensity variation analysis. We have analyzed the properties of color space defined by the International Commission on Illumination with the focus on the visual perception of the color components. Pixel features are obtained by using a color-size histogram for textural deviation analysis as the dominant property of the mathematical morphology, which has been performed for accurate segmentation of the tumor region. This approach is tested on 513 mammograms provided by digital database for screening mammography (DDSM) and the Mammographic Image Analysis Society (MIAS). In order to assess the performance of the proposed method, both the subjective as well as objective based approaches are used. The proposed method shows the prodigious performance in the mammogram segmentation process and achieved an accuracy rate of 98.00% on MIAS and 97.00% on DDSM images.