ArticleBioinformatics (Oxford, England)2011
The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 2 of them syntheses that pooled it.
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Who cites it
104 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Quality of reporting in AI cardiac MRI segmentation studies - A systematic review and recommendations for future studies.Frontiers in cardiovascular medicine · 2022Pooled it
- Society for Cardiovascular Magnetic Resonance (SCMR) expert consensus for CMR imaging endpoints in clinical research: part I - analytical validation and clinical qualification.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2018Guideline
- Imaging-anchored multiomics in cardiovascular disease: integrating cardiac imaging, bulk, single-cell, and spatial transcriptomics.Briefings in bioinformatics · 2026Review
- Self-powered intelligence for personalized healthcare.National science review · 2026Review
- Comprehensive evaluation of optimization algorithms for medical image segmentation.Scientific reports · 2025Article
- 3D cardiac shape analysis with variational point cloud autoencoders for myocardial infarction prediction and virtual heart synthesis.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2025Article
- Hybrid method for automatic initialization and segmentation of ventricular on large-scale cardiovascular magnetic resonance images.BMC medical imaging · 2025Article
- Automated three-dimensional left atrial analysis on computed tomography angiography: reproducibility and workflow efficiency of eight clinically relevant metrics using a deep learning pipeline.Frontiers in bioengineering and biotechnology · 2025Article
- SDF4CHD: Generative modeling of cardiac anatomies with congenital heart defects.Medical image analysis · 2024Article
- Semantic redundancy-aware implicit neural compression for multidimensional biomedical image data.Communications biology · 2024Article
- Differentiating Left Ventricular Remodeling in Aortic Stenosis From Systemic Hypertension.Circulation. Cardiovascular imaging · 2024Article
- Left Atrial Roof Enlargement Is a Distinct Feature of Heart Failure With Preserved Ejection Fraction.Circulation. Cardiovascular imaging · 2024Article
- MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models.Proceedings of the ... Conference on Fairness, Accountability, and Transparency · 2024Article
- Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways.Frontiers in physics · 2023Article
- Article
- The Potential of Deep Learning to Advance Clinical Applications of Computational Biomechanics.Bioengineering (Basel, Switzerland) · 2023Review
- Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease.Biophysics reviews · 2023Review
- A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2023Article
- Biventricular shape modes discriminate pulmonary valve replacement in tetralogy of Fallot better than imaging indices.Scientific reports · 2023Article
- Estimation of Cardiac Short Axis Slice Levels with a Cascaded Deep Convolutional and Recurrent Neural Network Model.Tomography (Ann Arbor, Mich.) · 2022Article
44 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
motivationIntegrative 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.
resultsThree 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.