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Self-parameterized active contours based on regional edge structure for medical image segmentation
This work introduces a novel framework for unsupervised parameterization of region-based active contour regularization and data fidelity terms, which is applied for medical image segmentation. The work aims to relieve MDs from the laborious, time-consuming task of empirical parameterization and bols...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4141071/ https://www.ncbi.nlm.nih.gov/pubmed/25152851 http://dx.doi.org/10.1186/2193-1801-3-424 |
_version_ | 1782331584042500096 |
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author | Mylona, Eleftheria A Savelonas, Michalis A Maroulis, Dimitris |
author_facet | Mylona, Eleftheria A Savelonas, Michalis A Maroulis, Dimitris |
author_sort | Mylona, Eleftheria A |
collection | PubMed |
description | This work introduces a novel framework for unsupervised parameterization of region-based active contour regularization and data fidelity terms, which is applied for medical image segmentation. The work aims to relieve MDs from the laborious, time-consuming task of empirical parameterization and bolster the objectivity of the segmentation results. The proposed framework is inspired by an observed isomorphism between the eigenvalues of structure tensors and active contour parameters. Both may act as descriptors of the orientation coherence in regions containing edges. The experimental results demonstrate that the proposed framework maintains a high segmentation quality without the need of trial-and-error parameter adjustment. |
format | Online Article Text |
id | pubmed-4141071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-41410712014-08-22 Self-parameterized active contours based on regional edge structure for medical image segmentation Mylona, Eleftheria A Savelonas, Michalis A Maroulis, Dimitris Springerplus Research This work introduces a novel framework for unsupervised parameterization of region-based active contour regularization and data fidelity terms, which is applied for medical image segmentation. The work aims to relieve MDs from the laborious, time-consuming task of empirical parameterization and bolster the objectivity of the segmentation results. The proposed framework is inspired by an observed isomorphism between the eigenvalues of structure tensors and active contour parameters. Both may act as descriptors of the orientation coherence in regions containing edges. The experimental results demonstrate that the proposed framework maintains a high segmentation quality without the need of trial-and-error parameter adjustment. Springer International Publishing 2014-08-11 /pmc/articles/PMC4141071/ /pubmed/25152851 http://dx.doi.org/10.1186/2193-1801-3-424 Text en © Mylona et al.; licensee Springer. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Research Mylona, Eleftheria A Savelonas, Michalis A Maroulis, Dimitris Self-parameterized active contours based on regional edge structure for medical image segmentation |
title | Self-parameterized active contours based on regional edge structure for medical image segmentation |
title_full | Self-parameterized active contours based on regional edge structure for medical image segmentation |
title_fullStr | Self-parameterized active contours based on regional edge structure for medical image segmentation |
title_full_unstemmed | Self-parameterized active contours based on regional edge structure for medical image segmentation |
title_short | Self-parameterized active contours based on regional edge structure for medical image segmentation |
title_sort | self-parameterized active contours based on regional edge structure for medical image segmentation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4141071/ https://www.ncbi.nlm.nih.gov/pubmed/25152851 http://dx.doi.org/10.1186/2193-1801-3-424 |
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