A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks-Reference-Cited by-同舟云学术

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A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks

Published:2018 Issue: Volume: Page:268-276
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
language:
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Author:

Tarroni Giacomo,Oktay Ozan,Sinclair Matthew,Bai Wenjia,Schuh Andreas,Suzuki Hideaki,de Marvao Antonio,O’Regan Declan,Cook Stuart,Rueckert Daniel

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-00928-1_31

Reference8 articles.

1. Lecture Notes in Computer Science;X Zhuang,2011

2. Lecture Notes in Computer Science;J Lötjönen,2004

3. Lecture Notes in Computer Science;M Sinclair,2017

4. Lecture Notes in Computer Science;D Yang,2017

5. Oktay, O., et al.: Respiratory motion correction for 2D cine cardiac MR images using probabilistic edge maps. In: Computing in Cardiology, pp. 129–132 (2016)

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1. Intensity-Based 3D Motion Correction for Cardiac MR Images;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

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

3. 3D MRI Cardiac Segmentation Under Respiratory Motion Artifacts;Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers;2022

4. Ensemble machine learning approach for screening of coronary heart disease based on echocardiography and risk factors;BMC Medical Informatics and Decision Making;2021-06-11

5. Deep Learning for Cardiac Image Segmentation: A Review;Frontiers in Cardiovascular Medicine;2020-03-05

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