Cardiac image modelling: Breadth and depth in heart disease-Reference-Cited by-同舟云学术

Cardiac image modelling: Breadth and depth in heart disease

Published:2016-10 Issue: Volume:33 Page:38-43
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Suinesiaputra Avan^ORCID,McCulloch Andrew D.,Nash Martyn P.^ORCID,Pontre Beau,Young Alistair A.^ORCID

Funder

National Heart Lung and Blood Institute

Health Research Council of New Zealand

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference26 articles.

1. The relationship of left ventricular mass and geometry to incident cardiovascular events: the MESA (Multi-Ethnic Study of Atherosclerosis) study;Bluemke;J. Am. Coll. Cardiol.,2008

2. Multiphysics and multiscale modelling, data–model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics;Chabiniok;Interface Focus,2016

3. The cardiac atlas project–an imaging database for computational modeling and statistical atlases of the heart;Fonseca;Bioinformatics,2011

4. Rapid D-Affine Biventricular Cardiac Function with Polar Prediction;Gilbert,2014

5. A three-dimensional finite element model of human atrial anatomy: new methods for cubic Hermite meshes with extraordinary vertices;Gonzales;Med. Image Anal.,2013

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Whole-heart modelling with valves in a fluid–structure interaction framework;Computer Methods in Applied Mechanics and Engineering;2024-02

2. Macroscale Modeling at the Organ Level;Multiscale Modelling in Biomedical Engineering;2023-05-04

3. A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot;Journal of Cardiovascular Magnetic Resonance;2023-02-27

4. Machine learning and biophysical models: how to benefit each other?;Reduced Order Models for the Biomechanics of Living Organs;2023

5. AI in the Real World;AI and Big Data in Cardiology;2023