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Microcalcification Segmentation from Mammograms: A Morphological Approach

This publication presents a computer method for segmenting microcalcifications in mammograms. It makes use of morphological transformations and is composed of two parts. The first part detects microcalcifications morphologically, thus allowing the approximate area of their occurrence to be determine...

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Autor principal: Ciecholewski, Marcin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359208/
https://www.ncbi.nlm.nih.gov/pubmed/27844218
http://dx.doi.org/10.1007/s10278-016-9923-8
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author Ciecholewski, Marcin
author_facet Ciecholewski, Marcin
author_sort Ciecholewski, Marcin
collection PubMed
description This publication presents a computer method for segmenting microcalcifications in mammograms. It makes use of morphological transformations and is composed of two parts. The first part detects microcalcifications morphologically, thus allowing the approximate area of their occurrence to be determined, the contrast to be improved, and noise to be reduced in the mammograms. In the second part, a watershed segmentation of microcalcifications is carried out. This study was carried out on a test set containing 200 ROIs 512 × 512 pixels in size, taken from mammograms from the Digital Database for Screening Mammography (DDSM), including 100 cases showing malignant lesions and 100 cases showing benign ones. The experiments carried out yielded the following average values of the measured indices: 80.5% (similarity index), 75.7% (overlap fraction), 70.8% (overlap value), and 19.8% (extra fraction). The average time of executing all steps of the methods used for a single ROI amounted to 0.83 s.
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spelling pubmed-53592082017-04-03 Microcalcification Segmentation from Mammograms: A Morphological Approach Ciecholewski, Marcin J Digit Imaging Article This publication presents a computer method for segmenting microcalcifications in mammograms. It makes use of morphological transformations and is composed of two parts. The first part detects microcalcifications morphologically, thus allowing the approximate area of their occurrence to be determined, the contrast to be improved, and noise to be reduced in the mammograms. In the second part, a watershed segmentation of microcalcifications is carried out. This study was carried out on a test set containing 200 ROIs 512 × 512 pixels in size, taken from mammograms from the Digital Database for Screening Mammography (DDSM), including 100 cases showing malignant lesions and 100 cases showing benign ones. The experiments carried out yielded the following average values of the measured indices: 80.5% (similarity index), 75.7% (overlap fraction), 70.8% (overlap value), and 19.8% (extra fraction). The average time of executing all steps of the methods used for a single ROI amounted to 0.83 s. Springer International Publishing 2016-11-14 2017-04 /pmc/articles/PMC5359208/ /pubmed/27844218 http://dx.doi.org/10.1007/s10278-016-9923-8 Text en © The Author(s) 2016 Open Access This 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 Article
Ciecholewski, Marcin
Microcalcification Segmentation from Mammograms: A Morphological Approach
title Microcalcification Segmentation from Mammograms: A Morphological Approach
title_full Microcalcification Segmentation from Mammograms: A Morphological Approach
title_fullStr Microcalcification Segmentation from Mammograms: A Morphological Approach
title_full_unstemmed Microcalcification Segmentation from Mammograms: A Morphological Approach
title_short Microcalcification Segmentation from Mammograms: A Morphological Approach
title_sort microcalcification segmentation from mammograms: a morphological approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359208/
https://www.ncbi.nlm.nih.gov/pubmed/27844218
http://dx.doi.org/10.1007/s10278-016-9923-8
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