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2016 | OriginalPaper | Chapter

An Overview of Pectoral Muscle Extraction Algorithms Applied to Digital Mammograms

Authors : Suhas Sapate, Sanjay Talbar

Published in: Medical Imaging in Clinical Applications

Publisher: Springer International Publishing

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Abstract

Substantial numbers of patients are reaching to a progressive breast cancer stage due to increase in the false negatives coming out of cumbersome and tedious job of continuously observing the mammograms in fatigue. Hence, the early detection of cancer with more accuracy is highly expected to reduce the death rate. Computer Aided Detection (CADe) can help radiologists in providing a second opinion increasing the overall accuracy of detection. Pectoral muscle is a predominant density area in most mammograms and may bias the results. Its extraction can increase accuracy and efficiency of cancer detection. This work is intended to provide the researchers a systematic and comprehensive overview of different techniques of pectoral muscle extraction which are categorized into groups based on intensity, region, gradient, transform, probability and polynomial, active contour, graph theory, and soft computing approaches. The performance of all these methods is summarized in tabular form for comparison purpose. The accuracy, efficiency and computational complexities of some selected methods are discussed in view of deciding a best approach in each of the categories.

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previous chapter Abdominal Imaging in Clinical Applications: Computer Aided Diagnosis Approaches

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Title: An Overview of Pectoral Muscle Extraction Algorithms Applied to Digital Mammograms
Authors: Suhas Sapate
Sanjay Talbar
Publisher: Springer International Publishing
Book: Medical Imaging in Clinical Applications
Print ISBN: 978-3-319-33791-3

Electronic ISBN: 978-3-319-33793-7

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-3-319-33793-7_2

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