22 August 2012 Statistical measures of orientation of texture for the detection of architectural distortion in prior mammograms of interval-cancer
Jayasree Chakraborty, Rangaraj M. Rangayyan, Shantanu Banik, Sudipta Mukhopadhyay, Joseph Edward Leo Desautels
Author Affiliations +
Abstract
Architectural distortion is an important sign of early breast cancer. Due to its subtlety, it is often missed during screening. We propose a method to detect architectural distortion in prior mammograms of interval-cancer cases based on statistical measures of oriented patterns. Oriented patterns were analyzed in the present work because regions with architectural distortion contain a large number of tissue structures spread over a wide angular range. Two new types of cooccurrence matrices were derived to estimate the joint occurrence of the angles of oriented structures. Statistical features were computed from each of the angle cooccurrence matrices to discriminate sites of architectural distortion from falsely detected regions in normal parts of mammograms. A total of 4,224 regions of interest (ROIs) were automatically obtained from 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases with the application of Gabor filters and phase portrait analysis. For each ROI, Haralick's 14 features were computed using the angle cooccurrence matrices. The best result obtained in terms of the area under the receiver operating characteristic (ROC) curve with the leave-one-patient-out method was 0.76; the free-response ROC curve indicated a sensitivity of 80% at 4.2 false positives per patient.
© 2012 SPIE and IS&T 0091-3286/2012/$25.00 © 2012 SPIE and IS&T
Jayasree Chakraborty, Rangaraj M. Rangayyan, Shantanu Banik, Sudipta Mukhopadhyay, and Joseph Edward Leo Desautels "Statistical measures of orientation of texture for the detection of architectural distortion in prior mammograms of interval-cancer," Journal of Electronic Imaging 21(3), 033010 (22 August 2012). https://doi.org/10.1117/1.JEI.21.3.033010
Published: 22 August 2012
Lens.org Logo
CITATIONS
Cited by 31 scholarly publications and 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Architectural distortion

Mammography

Breast cancer

Statistical analysis

Breast

Tissues

Feature extraction

Back to Top