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A vascular image registration method based on network structure and circuit simulation
BACKGROUND: Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to re...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414324/ https://www.ncbi.nlm.nih.gov/pubmed/28464789 http://dx.doi.org/10.1186/s12859-017-1649-1 |
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author | Chen, Li Lian, Yuxi Guo, Yi Wang, Yuanyuan Hatsukami, Thomas S. Pimentel, Kristi Balu, Niranjan Yuan, Chun |
author_facet | Chen, Li Lian, Yuxi Guo, Yi Wang, Yuanyuan Hatsukami, Thomas S. Pimentel, Kristi Balu, Niranjan Yuan, Chun |
author_sort | Chen, Li |
collection | PubMed |
description | BACKGROUND: Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. RESULTS: Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. CONCLUSIONS: The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods. |
format | Online Article Text |
id | pubmed-5414324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54143242017-05-03 A vascular image registration method based on network structure and circuit simulation Chen, Li Lian, Yuxi Guo, Yi Wang, Yuanyuan Hatsukami, Thomas S. Pimentel, Kristi Balu, Niranjan Yuan, Chun BMC Bioinformatics Research Article BACKGROUND: Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. RESULTS: Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. CONCLUSIONS: The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods. BioMed Central 2017-05-02 /pmc/articles/PMC5414324/ /pubmed/28464789 http://dx.doi.org/10.1186/s12859-017-1649-1 Text en © The Author(s). 2017 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Chen, Li Lian, Yuxi Guo, Yi Wang, Yuanyuan Hatsukami, Thomas S. Pimentel, Kristi Balu, Niranjan Yuan, Chun A vascular image registration method based on network structure and circuit simulation |
title | A vascular image registration method based on network structure and circuit simulation |
title_full | A vascular image registration method based on network structure and circuit simulation |
title_fullStr | A vascular image registration method based on network structure and circuit simulation |
title_full_unstemmed | A vascular image registration method based on network structure and circuit simulation |
title_short | A vascular image registration method based on network structure and circuit simulation |
title_sort | vascular image registration method based on network structure and circuit simulation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414324/ https://www.ncbi.nlm.nih.gov/pubmed/28464789 http://dx.doi.org/10.1186/s12859-017-1649-1 |
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