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Ziyu Li
DPhil Candidate
I am a DPhil candidate working under the supervision of Drs. Wenchuan Wu & Karla Miller at FMRIB Physics Group. My research focuses on developing novel acquisition and reconstruction methods for high-resolution diffusion MRI of in vivo human brain. I am also interested in exploring the potential of machine learning for enhancing MR image processing and analysis, such as denoising, contrast transfer, and diffusion modeling.
Before joining FMRIB, I obtained my Bachelor of Engineering and Bachelor of Management degrees from Tsinghua University in 2021. During my undergraduate studies, I also worked as a research intern at Martinos Center for Biomedical Imaging at Massachusetts General Hospital, Harvard Medical School from 2020 to 2021 (remotely due to the pandemic), with Drs. Qiyuan Tian & Susie Huang on developing deep learning methods for MRI analysis.
I am a member of Exeter College at Oxford. My DPhil study is fully funded by the Departmental Funding of Nuffield Department of Clinical Neurosciences.
Key publications
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Self-navigated 3D diffusion MRI using an optimized CAIPI sampling and
structured low-rank reconstruction
Preprint
Li Z. et al, (2024)
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Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high‐resolution 3D diffusion MRI
Journal article
Li Z. et al, (2023), Magnetic Resonance in Medicine
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Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat)
Journal article
Li Z. et al, (2023), Medical Image Analysis, 102744 - 102744
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High‐fidelity fast volumetric brain MRI using synergistic wave‐controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN)
Journal article
Li Z. et al, (2022), Medical Physics, 49, 1000 - 1014
Recent publications
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Self-navigated 3D diffusion MRI using an optimized CAIPI sampling and
structured low-rank reconstruction
Preprint
Li Z. et al, (2024)
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Structured low-rank reconstruction for navigator-free water/fat separated multi-shot diffusion-weighted EPI.
Journal article
Dong Y. et al, (2023), Magn Reson Med
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Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high‐resolution 3D diffusion MRI
Journal article
Li Z. et al, (2023), Magnetic Resonance in Medicine
-
Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high-resolution 3D diffusion MRI
Preprint
Li Z. et al, (2023)
-
Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat)
Journal article
Li Z. et al, (2023), Medical Image Analysis, 102744 - 102744