Share Email Print

Proceedings Paper

Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classification
Author(s): Rinku Rabidas; Abhishek Midya; Jayasree Chakraborty; Anup Sadhu; Wasim Arif
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, Curvelet based local attributes, Curvelet-Local configuration pattern (C-LCP), is introduced for the characterization of mammographic masses as benign or malignant. Amid different anomalies such as micro- calcification, bilateral asymmetry, architectural distortion, and masses, the reason for targeting the mass lesions is due to their variation in shape, size, and margin which makes the diagnosis a challenging task. Being efficient in classification, multi-resolution property of the Curvelet transform is exploited and local information is extracted from the coefficients of each subband using Local configuration pattern (LCP). The microscopic measures in concatenation with the local textural information provide more discriminating capability than individual. The measures embody the magnitude information along with the pixel-wise relationships among the neighboring pixels. The performance analysis is conducted with 200 mammograms of the DDSM database containing 100 mass cases of each benign and malignant. The optimal set of features is acquired via stepwise logistic regression method and the classification is carried out with Fisher linear discriminant analysis. The best area under the receiver operating characteristic curve and accuracy of 0.95 and 87.55% are achieved with the proposed method, which is further compared with some of the state-of-the-art competing methods.

Paper Details

Date Published: 27 February 2018
PDF: 6 pages
Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105752N (27 February 2018); doi: 10.1117/12.2293359
Show Author Affiliations
Rinku Rabidas, National Institute of Technology, Silchar (India)
Abhishek Midya, Memorial Sloan-Kettering Cancer Ctr. (United States)
Jayasree Chakraborty, Memorial Sloan-Kettering Cancer Ctr. (United States)
Anup Sadhu, Medical College Kolkata (India)
Wasim Arif, National Institute of Technology, Silchar (India)

Published in SPIE Proceedings Vol. 10575:
Medical Imaging 2018: Computer-Aided Diagnosis
Nicholas Petrick; Kensaku Mori, Editor(s)

© SPIE. Terms of Use
Back to Top