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A Study of Different Texture Features Based on Local Operator for Benign-malignant Mass Classification.

Authors :
Rabidas, Rinku
Midya, Abhishek
Chakraborty, Jayasree
Arif, Wasim
Source :
Procedia Computer Science; 2016, Vol. 93, p389-395, 7p
Publication Year :
2016

Abstract

In this paper, a comparative analysis of different texture features based on local operator has been produced for the determination of mammographic masses as benign or malignant. Local Binary Pattern (LBP), LBP Variance (LBPV), and Completed LBP (CLBP) descriptors are extracted to evaluate their potential for mass classification in a Computer-Aided Diagnosis (CAD) system. An Az value of 0 . 97 ± 0 . 02 and an accuracy of 92 . 25 ± 0 . 01% have been achieved, while experimenting on 200 mass cases from the DDSM database, by selecting the optimal set of features employing stepwise logistic regression method, followed by classification via Fisher Linear Discriminant Analysis (FLDA) using 10-fold cross validation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
93
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
117439638
Full Text :
https://doi.org/10.1016/j.procs.2016.07.225