Please use this identifier to cite or link to this item:
Title: Comparative analysis of breast cancer detection in mammograms and thermograms
Authors: Milosevic, Marina
Jankovic, Dragan
Peulic A.
Issue Date: 2015
Abstract: © 2015, Walter de Gruyter GmbH. All rights reserved. In this paper, we present a system based on feature extraction techniques for detecting abnormal patterns in digital mammograms and thermograms. A comparative study of texture-analysis methods is performed for three image groups: mammograms from the Mammographic Image Analysis Society mammographic database; digital mammograms from the local database; and thermography images of the breast. Also, we present a procedure for the automatic separation of the breast region from the mammograms. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 texture features are extracted from the region of interest. The ability of feature set in differentiating abnormal from normal tissue is investigated using a support vector machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross-validation method and receiver operating characteristic analysis was performed.
Type: article
DOI: 10.1515/bmt-2014-0047
ISSN: 0013-5585
SCOPUS: 2-s2.0-84925344935
Appears in Collections:Faculty of Technical Sciences, Čačak

Page views(s)




Files in This Item:
File Description SizeFormat 
  Restricted Access
29.86 kBAdobe PDFThumbnail

Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.