Mammography visual enhancement in CAD-based breast cancer diagnosis

Hongting Wang; Jun-Bao Li; Ligang Wu; Huijun Gao

doi:10.1016/j.clinimag.2012.04.018

Mammography visual enhancement in CAD-based breast cancer diagnosis

Clin Imaging. 2013 Mar-Apr;37(2):273-82. doi: 10.1016/j.clinimag.2012.04.018. Epub 2012 Jun 8.

Authors

Hongting Wang¹, Jun-Bao Li, Ligang Wu, Huijun Gao

Affiliation

¹ Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, China.

PMID: 23465979
DOI: 10.1016/j.clinimag.2012.04.018

Abstract

This paper presents a novel approach to detect and discriminate abnormal and cueing signatures in mammography through enhancing the imaging contrast. Partial gland and adipose tissues are removed, and thus, the visual effect of mammography will be enhanced. Inspired by single image haze removal, we remove the majority of background tissues by introducing the idea of image matting. Experimental results show the feasibility and performance on distinguishing focuses from healthy tissues in the enhanced mammography. The method has potential applications on breast cancer diagnosis in computer-aided detection.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Breast Neoplasms / diagnostic imaging*
Diagnosis, Computer-Assisted / methods*
Female
Humans
Mammography*
Radiographic Image Enhancement / methods*
Subtraction Technique