Paper Info
Title
A novel multistage system for the detection and removal of pectoral muscles in mammograms
Abstract
In this paper, a novel multistage scheme for pectoral muscle removal from mammography images is proposed, and the performance of this system is verified using the publicly available Mammographic Image Analysis Society digital mammogram database. This database is composed of mediolateral oblique mammography images including three different tissue types (fatty, fatty-glandular, and dense-glandular) with three health status types (normal, benign cancer, and malignant cancer). In the implementation of the proposed system, a mammography image is first preprocessed by performing noise reduction background removal followed by artifact suppression processes. Then a presegmentation procedure is applied using region growing and line fitting is executed. Finally, pixels including pectoral muscle regions are removed from mammography images with an accuracy of 94.40%, sensitivity of 89.62%, and specificity of 99.99% after some postprocessing operations. Although the mean false positive rate obtained by the proposed approach is higher than that of other studies in the literature, not only the lower mean false negative rate but also the enhancement in the quality of pectoral muscle segmentation for all 322 images in the database evidently show the success of the proposed approach.
Year
DOI
Venue
2018
10.3906/elk-1703-272
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
Keywords
DocType
Volume
Breast cancer,pectoral muscle removal,computer aided diagnosis,digital mammography
Journal
26
Issue
ISSN
Citations 
1.0
1300-0632
0
PageRank 
References 
Authors
0.34
14
3
Name
Order
Citations
PageRank
İdil Işikli Esener100.34
Semih Ergin2264.00
Tolga Yüksel3172.53