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Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement
Image processing methods significantly contribute to visualization of images captured by biomedical modalities (such as mammography, X-ray computed tomography, magnetic resonance imaging, and light and electron microscopy). Quantitative interpretation of the deluge of complicated biomedical images,...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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International Union of Crystallography
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3795542/ https://www.ncbi.nlm.nih.gov/pubmed/24121326 http://dx.doi.org/10.1107/S0909049513020761 |
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author | Kimori, Yoshitaka |
author_facet | Kimori, Yoshitaka |
author_sort | Kimori, Yoshitaka |
collection | PubMed |
description | Image processing methods significantly contribute to visualization of images captured by biomedical modalities (such as mammography, X-ray computed tomography, magnetic resonance imaging, and light and electron microscopy). Quantitative interpretation of the deluge of complicated biomedical images, however, poses many research challenges, one of which is to enhance structural features that are scarcely perceptible to the human eye. This study introduces a contrast enhancement approach based on a new type of mathematical morphology called rotational morphological processing. The proposed method is applied to medical images for the enhancement of structural features. The effectiveness of the method is evaluated quantitatively by the contrast improvement ratio (CIR). The CIR of the proposed method is 12.1, versus 4.7 and 0.1 for two conventional contrast enhancement methods, clearly indicating the high contrasting capability of the method. |
format | Online Article Text |
id | pubmed-3795542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-37955422013-10-15 Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement Kimori, Yoshitaka J Synchrotron Radiat Diffraction Structural Biology Image processing methods significantly contribute to visualization of images captured by biomedical modalities (such as mammography, X-ray computed tomography, magnetic resonance imaging, and light and electron microscopy). Quantitative interpretation of the deluge of complicated biomedical images, however, poses many research challenges, one of which is to enhance structural features that are scarcely perceptible to the human eye. This study introduces a contrast enhancement approach based on a new type of mathematical morphology called rotational morphological processing. The proposed method is applied to medical images for the enhancement of structural features. The effectiveness of the method is evaluated quantitatively by the contrast improvement ratio (CIR). The CIR of the proposed method is 12.1, versus 4.7 and 0.1 for two conventional contrast enhancement methods, clearly indicating the high contrasting capability of the method. International Union of Crystallography 2013-11-01 2013-09-25 /pmc/articles/PMC3795542/ /pubmed/24121326 http://dx.doi.org/10.1107/S0909049513020761 Text en © Yoshitaka Kimori 2013 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Diffraction Structural Biology Kimori, Yoshitaka Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
title | Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
title_full | Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
title_fullStr | Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
title_full_unstemmed | Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
title_short | Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
title_sort | morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement |
topic | Diffraction Structural Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3795542/ https://www.ncbi.nlm.nih.gov/pubmed/24121326 http://dx.doi.org/10.1107/S0909049513020761 |
work_keys_str_mv | AT kimoriyoshitaka morphologicalimageprocessingforquantitativeshapeanalysisofbiomedicalstructureseffectivecontrastenhancement |