Open AccessBreast Cancer Detection Using Combination of Feature Extraction Models
Author(s) -
T. Suneetha Rani,
S J Soujanya,
P. Anjaiah
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.12.16549
Subject(s) - artificial intelligence , segmentation , computer science , region of interest , pattern recognition (psychology) , feature extraction , feature (linguistics) , computer vision , breast cancer , image segmentation , mammography , filter (signal processing) , cancer , medicine , philosophy , linguistics
Recognition of either masses or tissues in a mammogram digital images is a key issue for radiologist. Present methods uses medial filter and morphological operations for detection of suspected cases in a mammogram. They use region of interest (ROI) segmentation for extraction of masses and classification of levels of severities. Classification of large number of mammogram images based on breast cancer cases takes longer computation time for performing of ROI segmentation. This is addressed by multi-ROI segmentation and it retrieves the textual properties of large mammogram images for effectively determining the breast cancer mammogram images.Experimental results shows the better performance of proposed method than existing ROI based texture feature extraction.