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The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart
Motivation: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of non...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3150036/ https://www.ncbi.nlm.nih.gov/pubmed/21737439 http://dx.doi.org/10.1093/bioinformatics/btr360 |
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author | Fonseca, Carissa G. Backhaus, Michael Bluemke, David A. Britten, Randall D. Chung, Jae Do Cowan, Brett R. Dinov, Ivo D. Finn, J. Paul Hunter, Peter J. Kadish, Alan H. Lee, Daniel C. Lima, Joao A. C. Medrano−Gracia, Pau Shivkumar, Kalyanam Suinesiaputra, Avan Tao, Wenchao Young, Alistair A. |
author_facet | Fonseca, Carissa G. Backhaus, Michael Bluemke, David A. Britten, Randall D. Chung, Jae Do Cowan, Brett R. Dinov, Ivo D. Finn, J. Paul Hunter, Peter J. Kadish, Alan H. Lee, Daniel C. Lima, Joao A. C. Medrano−Gracia, Pau Shivkumar, Kalyanam Suinesiaputra, Avan Tao, Wenchao Young, Alistair A. |
author_sort | Fonseca, Carissa G. |
collection | PubMed |
description | Motivation: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups. Results: Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt). Availability: http://www.cardiacatlas.org Contact: a.young@auckland.ac.nz Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3150036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31500362011-08-08 The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart Fonseca, Carissa G. Backhaus, Michael Bluemke, David A. Britten, Randall D. Chung, Jae Do Cowan, Brett R. Dinov, Ivo D. Finn, J. Paul Hunter, Peter J. Kadish, Alan H. Lee, Daniel C. Lima, Joao A. C. Medrano−Gracia, Pau Shivkumar, Kalyanam Suinesiaputra, Avan Tao, Wenchao Young, Alistair A. Bioinformatics Original Papers Motivation: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups. Results: Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt). Availability: http://www.cardiacatlas.org Contact: a.young@auckland.ac.nz Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2011-08-15 2011-07-06 /pmc/articles/PMC3150036/ /pubmed/21737439 http://dx.doi.org/10.1093/bioinformatics/btr360 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Fonseca, Carissa G. Backhaus, Michael Bluemke, David A. Britten, Randall D. Chung, Jae Do Cowan, Brett R. Dinov, Ivo D. Finn, J. Paul Hunter, Peter J. Kadish, Alan H. Lee, Daniel C. Lima, Joao A. C. Medrano−Gracia, Pau Shivkumar, Kalyanam Suinesiaputra, Avan Tao, Wenchao Young, Alistair A. The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart |
title | The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart |
title_full | The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart |
title_fullStr | The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart |
title_full_unstemmed | The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart |
title_short | The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart |
title_sort | cardiac atlas project—an imaging database for computational modeling and statistical atlases of the heart |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3150036/ https://www.ncbi.nlm.nih.gov/pubmed/21737439 http://dx.doi.org/10.1093/bioinformatics/btr360 |
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