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Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images

BACKGROUND: Dual-source computed tomography (DSCT) is a very effective way for diagnosis and treatment of heart disease. The quantitative information of spatiotemporal DSCT images can be important for the evaluation of cardiac function. To avoid the shortcoming of manual delineation, it is imperativ...

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Autores principales: Lu, Xuesong, Yang, Rongqian, Xie, Qinlan, Ou, Shanxing, Zha, Yunfei, Wang, Defeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370472/
https://www.ncbi.nlm.nih.gov/pubmed/28351368
http://dx.doi.org/10.1186/s12938-017-0323-1
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author Lu, Xuesong
Yang, Rongqian
Xie, Qinlan
Ou, Shanxing
Zha, Yunfei
Wang, Defeng
author_facet Lu, Xuesong
Yang, Rongqian
Xie, Qinlan
Ou, Shanxing
Zha, Yunfei
Wang, Defeng
author_sort Lu, Xuesong
collection PubMed
description BACKGROUND: Dual-source computed tomography (DSCT) is a very effective way for diagnosis and treatment of heart disease. The quantitative information of spatiotemporal DSCT images can be important for the evaluation of cardiac function. To avoid the shortcoming of manual delineation, it is imperative to develop an automatic segmentation technique for 4D cardiac images. METHODS: In this paper, we implement the heart segmentation-propagation framework based on nonrigid registration. The corresponding points of anatomical substructures are extracted by using the extension of n-dimensional scale invariant feature transform method. They are considered as a constraint term of nonrigid registration using the free-form deformation, in order to restrain the large variations and boundary ambiguity between subjects. RESULTS: We validate our method on 15 patients at ten time phases. Atlases are constructed by the training dataset from ten patients. On the remaining data the median overlap is shown to improve significantly compared to original mutual information, in particular from 0.4703 to 0.5015 ([Formula: see text] ) for left ventricle myocardium and from 0.6307 to 0.6519 ([Formula: see text] ) for right atrium. CONCLUSIONS: The proposed method outperforms standard mutual information of intensity only. The segmentation errors had been significantly reduced at the left ventricle myocardium and the right atrium. The mean surface distance of using our framework is around 1.73 mm for the whole heart.
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spelling pubmed-53704722017-03-30 Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images Lu, Xuesong Yang, Rongqian Xie, Qinlan Ou, Shanxing Zha, Yunfei Wang, Defeng Biomed Eng Online Research BACKGROUND: Dual-source computed tomography (DSCT) is a very effective way for diagnosis and treatment of heart disease. The quantitative information of spatiotemporal DSCT images can be important for the evaluation of cardiac function. To avoid the shortcoming of manual delineation, it is imperative to develop an automatic segmentation technique for 4D cardiac images. METHODS: In this paper, we implement the heart segmentation-propagation framework based on nonrigid registration. The corresponding points of anatomical substructures are extracted by using the extension of n-dimensional scale invariant feature transform method. They are considered as a constraint term of nonrigid registration using the free-form deformation, in order to restrain the large variations and boundary ambiguity between subjects. RESULTS: We validate our method on 15 patients at ten time phases. Atlases are constructed by the training dataset from ten patients. On the remaining data the median overlap is shown to improve significantly compared to original mutual information, in particular from 0.4703 to 0.5015 ([Formula: see text] ) for left ventricle myocardium and from 0.6307 to 0.6519 ([Formula: see text] ) for right atrium. CONCLUSIONS: The proposed method outperforms standard mutual information of intensity only. The segmentation errors had been significantly reduced at the left ventricle myocardium and the right atrium. The mean surface distance of using our framework is around 1.73 mm for the whole heart. BioMed Central 2017-03-28 /pmc/articles/PMC5370472/ /pubmed/28351368 http://dx.doi.org/10.1186/s12938-017-0323-1 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
Lu, Xuesong
Yang, Rongqian
Xie, Qinlan
Ou, Shanxing
Zha, Yunfei
Wang, Defeng
Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images
title Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images
title_full Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images
title_fullStr Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images
title_full_unstemmed Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images
title_short Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images
title_sort nonrigid registration with corresponding points constraint for automatic segmentation of cardiac dsct images
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370472/
https://www.ncbi.nlm.nih.gov/pubmed/28351368
http://dx.doi.org/10.1186/s12938-017-0323-1
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