Detection and Segmentation of Pectoral Muscle on MLO-View Mammogram Using Enhancement Filter

The presence of predominant density region of the pectoral muscle in Medio-Lateral Oblique (MLO) view of the mammograms can affect or bias the results of mammograms processing for breast cancer detection using intensity based methods. Therefore, to improve the diagnostic performance of breast cancer...

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Bibliographic Details
Published in:Journal of medical systems 2017-12, Vol.41 (12), p.190-13, Article 190
Main Authors: Vikhe, P. S., Thool, V. R.
Format: Article
Language:English
Subjects:
Breast cancer
Breasts
Cancer
Curve fitting
Diagnostic systems
Health Informatics
Health Sciences
Image analysis
Image processing
Image segmentation
Mammography
Medicine
Medicine & Public Health
Muscles
Performance evaluation
Statistics for Life Sciences
Transactional Processing Systems
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Summary:The presence of predominant density region of the pectoral muscle in Medio-Lateral Oblique (MLO) view of the mammograms can affect or bias the results of mammograms processing for breast cancer detection using intensity based methods. Therefore, to improve the diagnostic performance of breast cancer detection using computer-aided system, identification and segmentation of pectoral muscle is an important task. This paper presents, an intensity based approach to identify the pectoral region in mammograms. In the presented approach enhancement mask and threshold technique is used to enhance and select the pectoral region and boundary points respectively, to find the boundary of pectoral muscle. Then curve fitting by Least Square Error (LSE) method is used to refine the rough initial boundaries. The proposed approach was applied on 320 mammograms from mini-Mammographic Image Analysis Society (mini-MIAS) database of 322 mammograms, with acceptable rate of 96.56% from radiologist experts. The performance evaluation for pectoral muscle segmentation, based on Hausdorff distance (H d ), False Positive (FP) and False Negative (FN) rate, shows the usefulness and effectiveness of the proposed approach.
ISSN:0148-5598
1573-689X
DOI:10.1007/s10916-017-0839-8