👨🎓 I’m Jiyao Liu (刘继垚), currently a third-year Ph.D. student majoring in Biomedical Engineering at Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University. I am honored to be advised by Prof. Dr. Xiahai Zhuang and Dr. Ningsheng Xu. Previously, I received the Bachelor’s degree (June 2022) in Intelligence Science and Technology from Xidian University.
🔭 Research interests
My research interest includes AI in Medical Imaging and Generative Model, e.g., trustworthy multimodal medical image synthesis, generalizable MRI reconstruction / inverse problem in medical imaging. At present, I devote to enhancing the reliability and generalizability of medical image reconstruction.
🔥 News
- 2023.10: 🎉🎉 One paper has been oral reported on SASHIMI, MICCAI workshop, 2023.
- 2021.12: I started my research on Cross-modality face recognition with Dr. Qigong Sun from SenseTime Group.
- 2021.05: 🎉🎉 MCM/ICM, Mathematical Contest in Modeling, Outstanding Winner🎉（美国大学生数学建模竞赛特等奖，O奖）
📝 Publications
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A New Framework of Implicit Prior Adaptation for Boosting Test-Time MRI Reconstruction
Jiyao Liu, Shangqi Gao, Xiao-Yong Zhang, Ningsheng Xu and Xiahai Zhuang
- In this work, we propose a zero-shot adaptation framework tailored to the reference phase of an implicit prior-based MRI reconstruction model. This framework is designed to seamlessly integrate with any contemporary implicit prior-based methods without modifying their architectures or pre-trained weights. Our approach requires only the automatic adjustment of three scaling factors during inference.
Trustworthy Contrast-enhanced Brain MRI Synthesis with Deep Evidential Regression
Jiyao Liu, Yuxin Li, Shangqi Gao, Yuncheng Zhou, Ningsheng Xu, Xiao-Yong Zhang, and Xiahai Zhuang
- In this work, we propose a new method that approaches multi-to-one medical image translation as a multimodal regression problem for brain CE-MRI synthesis. We developed an uncertainty-aware framework using deep evidential regression with uncertainty calibration and incorporated source modality fusion to improve performance, reliability, and interpretability.
Multi-Phase Liver-Specific DCE-MRI Translation via a Registration-Guided GAN
Jiyao Liu, Yuxin Li, Nannan Shi, Yuncheng Zhou, Shangqi Gao, Yuxin Shi , Xiao-Yong Zhang, Xiahai Zhuang
- This paper introduces a new dataset and a novel application of image translation from multi-phase DCE-MRIs into a virtual GED- HBP image (v-HBP) that could be used as a substitute for GED-HBP in clinical liver diagnosis.
🎖 Honors and Awards
- 2022.06 Undergraduate Excellence Award.
- 2021.05 MCM/ICM, Mathematical Contest in Modeling, Outstanding Winner | [blog] | [github].
- 2019/2020/2021 National Endeavor Scholarship (BSc), Xidian University.
📖 Educations
- 2022.09 - 2027.06 (now), P.h.d., Fudan University, Shanghai.
- 2018.09 - 2022.06, B.S., Xi Dian University, Xi’an.
💬 Invited Talks
- 2023.10, Oral report | International Workshop on Simulation and Synthesis in Medical Imaging (SASHIMI) ,MICCAI workshop, 2023.
- 2021.03, Oral report | International Society for Magnetic Resonance in Medicine (ISMRM)
💻 Internships
- 2021.12 - 2022.06, Sensetime（商汤科技，算法实习生）, Xi’an.
Daily Life
