Paper Info
Title
Classification of breast tissues using Moran's index and Geary's coefficient as texture signatures and SVM
Abstract
Female breast cancer is the major cause of cancer-related deaths in western countries. Efforts in computer vision have been made in order to help improving the diagnostic accuracy by radiologists. In this paper, we present a methodology that uses Moran's index and Geary's coefficient measures in breast tissues extracted from mammogram images. These measures are used as input features for a support vector machine classifier with the purpose of distinguishing tissues between normal and abnormal cases as well as classifying them into benign and malignant cancerous cases. The use of both proposed techniques showed to be very promising, since we obtained an accuracy of 96.04% and Az ROC of 0.946 with Geary's coefficient and an accuracy of 99.39% and Az ROC of 1 with Moran's index to discriminate tissues in mammograms as normal or abnormal. We also obtained accuracy of 88.31% and Az ROC of 0.804 with Geary's coefficient and accuracy of 87.80% and Az ROC of 0.89 with Moran's index to discriminate tissues in mammograms as benign and malignant.
Year
DOI
Venue
2009
10.1016/j.compbiomed.2009.08.009
Comp. in Bio. and Med.
Keywords
DocType
Volume
Mammography,Breast tissue classification,Moran's index,Geary's coefficient,Support vector machine
Journal
39
Issue
ISSN
Citations 
12
0010-4825
33
PageRank 
References 
Authors
1.16
14
4
Name
Order
Citations
PageRank
Geraldo Braz Junior17615.10
Anselmo C. Paiva237948.88
Aristofanes C. Silva331636.48
Alexandre César Muniz De Oliveira4838.30