Embedding-Alignment Fusion-Based Graph Convolution Network With Mixed Learning Strategy for 4D Medical Image Reconstruction-Reference-Cited by-同舟云学术

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Embedding-Alignment Fusion-Based Graph Convolution Network With Mixed Learning Strategy for 4D Medical Image Reconstruction

Published:2024-05 Issue:5 Volume:28 Page:2916-2929
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Li Jingshu¹^ORCID,Fu Tianyu²^ORCID,Song Hong³^ORCID,Fan Jingfan¹^ORCID,Xiao Deqiang¹^ORCID,Lin Yucong²^ORCID,Gu Ying²^ORCID,Yang Jian¹^ORCID

Affiliation:

1. School of Optics and Photonics, Beijing Institute of Technology, Beijing, China

2. School of Medical Technology, Beijing Institute of Technology, Beijing, China

3. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

Funder

National Key R&D Program of China

National Science Foundation Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221020/10521573/10458299.pdf?arnumber=10458299

Reference37 articles.

1. Autoadaptive motion modelling for MR-based respiratory motion estimation

2. Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT

3. Manifold learning for image-based breathing gating in ultrasound and MRI

4. MRI-based motion correction of thoracic PET: initial comparison of acquisition protocols and correction strategies suitable for simultaneous PET/MRI systems

5. 4D Ultrasound Tracking of Liver and its Verification for TIPS Guidance

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