Ventricle Surface Reconstruction from Cardiac MR Slices Using Deep Learning-Reference-Cited by-同舟云学术

Ventricle Surface Reconstruction from Cardiac MR Slices Using Deep Learning

Published:2019 Issue: Volume: Page:342-351
ISSN:0302-9743
Container-title:Functional Imaging and Modeling of the Heart
language:
Short-container-title:

Author:

Xu Hao,Zacur Ernesto,Schneider Jurgen E.,Grau Vicente

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-21949-9_37

Reference26 articles.

1. Vukicevic, M., Mosadegh, B., Min, J., Little, S.: Cardiac 3D printing and its future directions. JACC Cardiovasc. Imaging 10, 171–184 (2017)

2. Suinesiaputra, A., et al.: Statistical shape modeling of the left ventricle: myocardial infarct classification challenge. IEEE JBHI 22(2), 503–515 (2018)

3. Lecture Notes in Computer Science;H Lehmann,2009

4. Lecture Notes in Computer Science;E Zacur,2017

5. Arevalo, H., et al.: Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models. Nat. Commun. 7, 11437 (2016)

Cited by 15 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. Motion correction and super-resolution for multi-slice cardiac magnetic resonance imaging via an end-to-end deep learning approach;Computerized Medical Imaging and Graphics;2024-07

2. Motion Correction and Super-Resolution for Multi-slice Cardiac Magnetic Resonance Imaging via a Multi-stage Deep Learning Approach;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

3. Evaluation of deep learning estimation of whole heart anatomy from automated cardiovascular magnetic resonance short- and long-axis analyses in UK Biobank;European Heart Journal - Cardiovascular Imaging;2024-05-09

4. Neural Implicit Functions for 3D Shape Reconstruction from Standard Cardiovascular Magnetic Resonance Views;Lecture Notes in Computer Science;2024

5. Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images;Medical Image Analysis;2023-12