Zi Wang
Orcid: 0000-0001-8635-8334Affiliations:
- Xiamen University, National Institute for Data Science in Health and Medicine, Department of Electronic Science, China
According to our database1,
Zi Wang
authored at least 29 papers
between 2020 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on orcid.org
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Bibliography
2026
Diffusion-prior based implicit neural representation for arbitrary-scale cardiac cine MRI super-resolution.
Inf. Fusion, 2026
2025
DRIMV_TSK: An Interpretable Surgical Evaluation Model for Incomplete Multi-View Rectal Cancer Data.
CoRR, June, 2025
From Coarse to Continuous: Progressive Refinement Implicit Neural Representation for Motion-Robust Anisotropic MRI Reconstruction.
CoRR, June, 2025
One for multiple: Physics-informed synthetic data boosts generalizable deep learning for fast MRI reconstruction.
Medical Image Anal., 2025
The state-of-the-art in cardiac MRI reconstruction: Results of the CMRxRecon challenge in MICCAI 2023.
Medical Image Anal., 2025
2024
BMC Medical Imaging, December, 2024
IEEE J. Biomed. Health Informatics, April, 2024
CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists' Image Quality Evaluation.
IEEE Trans. Cloud Comput., 2024
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI.
CoRR, 2024
Simultaneous Deep Learning of Myocardium Segmentation and T2 Quantification for Acute Myocardial Infarction MRI.
CoRR, 2024
A 1D Plug-and-Play Synthetic Data Deep Learning For Undersampled Magnetic Resonance Image Reconstruction.
Proceedings of the IEEE International Conference on Image Processing, 2024
2023
IEEE Trans. Biomed. Eng., December, 2023
A Sparse Model-Inspired Deep Thresholding Network for Exponential Signal Reconstruction - Application in Fast Biological Spectroscopy.
IEEE Trans. Neural Networks Learn. Syst., October, 2023
IEEE Trans. Neural Networks Learn. Syst., September, 2023
Physics-Driven Synthetic Data Learning for Biomedical Magnetic Resonance: The imaging physics-based data synthesis paradigm for artificial intelligence.
IEEE Signal Process. Mag., March, 2023
IEEE Trans. Medical Imaging, 2023
XCloud-VIP: Virtual Peak Enables Highly Accelerated NMR Spectroscopy and Faithful Quantitative Measures.
IEEE Trans. Computational Imaging, 2023
IEEE Trans. Computational Imaging, 2023
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction.
CoRR, 2023
One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction.
CoRR, 2023
Physics-informed Deep Diffusion MRI Reconstruction: Break the Bottleneck of Training Data in Artificial Intelligence.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
2021
A partial sum of singular-value-based reconstruction method for non-uniformly sampled NMR spectroscopy.
IET Signal Process., 2021
BMC Medical Imaging, 2021
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Accelerated image reconstruction with separable Hankel regularization in parallel MRI.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
2020
CoRR, 2020