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Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms
The detection of the pectoral muscle boundary in the medio-lateral oblique view of mammograms is essential to improving the computer-aided diagnosis of breast cancer. In this study, a shape-based detection method is proposed for accurately extracting the boundary of the pectoral muscle in mammograms...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491117/ https://www.ncbi.nlm.nih.gov/pubmed/26167142 http://dx.doi.org/10.1007/s40846-015-0043-6 |
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author | Chen, Chunxiao Liu, Gao Wang, Jing Sudlow, Gail |
author_facet | Chen, Chunxiao Liu, Gao Wang, Jing Sudlow, Gail |
author_sort | Chen, Chunxiao |
collection | PubMed |
description | The detection of the pectoral muscle boundary in the medio-lateral oblique view of mammograms is essential to improving the computer-aided diagnosis of breast cancer. In this study, a shape-based detection method is proposed for accurately extracting the boundary of the pectoral muscle in mammograms. A shape-based enhancement mask is applied to the mammogram and the initial boundary is then defined using morphological operators. The seed point is then detected on the initial boundary and the pectoral boundary is evolved from candidate points produced using a shape-based growth strategy. A cubic polynomial fitting function is implemented to obtain the final pectoral muscle boundary. The proposed method was applied to 322 mammograms from the mini Mammographic Image Analysis Society database. A 97.2 % acceptable rate from expert radiologists and assessment results based on the false positive rate, false negative rate, and Hausdorff distance demonstrate the robustness and effectiveness of the proposed shape-based detection method. |
format | Online Article Text |
id | pubmed-4491117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-44911172015-07-08 Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms Chen, Chunxiao Liu, Gao Wang, Jing Sudlow, Gail J Med Biol Eng Original Article The detection of the pectoral muscle boundary in the medio-lateral oblique view of mammograms is essential to improving the computer-aided diagnosis of breast cancer. In this study, a shape-based detection method is proposed for accurately extracting the boundary of the pectoral muscle in mammograms. A shape-based enhancement mask is applied to the mammogram and the initial boundary is then defined using morphological operators. The seed point is then detected on the initial boundary and the pectoral boundary is evolved from candidate points produced using a shape-based growth strategy. A cubic polynomial fitting function is implemented to obtain the final pectoral muscle boundary. The proposed method was applied to 322 mammograms from the mini Mammographic Image Analysis Society database. A 97.2 % acceptable rate from expert radiologists and assessment results based on the false positive rate, false negative rate, and Hausdorff distance demonstrate the robustness and effectiveness of the proposed shape-based detection method. Springer Berlin Heidelberg 2015-06-10 2015 /pmc/articles/PMC4491117/ /pubmed/26167142 http://dx.doi.org/10.1007/s40846-015-0043-6 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Chen, Chunxiao Liu, Gao Wang, Jing Sudlow, Gail Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms |
title | Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms |
title_full | Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms |
title_fullStr | Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms |
title_full_unstemmed | Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms |
title_short | Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms |
title_sort | shape-based automatic detection of pectoral muscle boundary in mammograms |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491117/ https://www.ncbi.nlm.nih.gov/pubmed/26167142 http://dx.doi.org/10.1007/s40846-015-0043-6 |
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