Share Email Print
cover

Proceedings Paper

Detection of architectural distortion in prior mammograms using measures of angular distribution
Author(s): Rangaraj M. Rangayyan; Shantanu Banik; J. E. L. Desautels
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

We present methods for the detection of architectural distortion in mammograms of interval-cancer cases taken prior to the diagnosis of breast cancer using measures of angular distribution derived from Gabor filter responses in magnitude and angle, coherence, orientation strength, and the angular spread of power in the Fourier spectrum. A total of 4224 regions of interest (ROIs) were automatically obtained using Gabor filters and phase portrait analysis from 106 prior mammograms of 56 interval-cancer cases with 301 ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. Images of coherence and orientation strength were derived from the Gabor responses in magnitude and orientation. Each ROI was represented by the entropy of the angular histogram composed with the Gabor magnitude response, angle, coherence, and orientation strength; the entropy of the angular spread of power in the Fourier spectrum was also computed. Using stepwise logistic regression for feature selection and the leave-one-image-out method in feature selection and pattern classification, the area under the receiver operating characteristic curve of 0.76 was obtained with an artificial neural network based on radial basis functions. Analysis of the free-response receiver operating characteristics indicated 82% sensitivity at 7.2 false positives per image.

Paper Details

Date Published: 4 March 2011
PDF: 9 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 796308 (4 March 2011); doi: 10.1117/12.877587
Show Author Affiliations
Rangaraj M. Rangayyan, Univ. of Calgary (Canada)
Shantanu Banik, Univ. of Calgary (Canada)
J. E. L. Desautels, Univ. of Calgary (Canada)


Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers; Bram van Ginneken, Editor(s)

© SPIE. Terms of Use
Back to Top