Yuhang Liu's Homepage

Yuhang Liu (刘宇航)

I am an R&D Expert leading a cross-disciplinary AI team at YIZHUN, a fast-growing startup driving innovation in AI-powered medical imaging that has reached Series D funding. We have built multiple AI medical imaging products from the ground up, established a complete pipeline from data governance to commercial deployment, achieved National Medical Products Administration (NMPA) Class III certification, secured 20+ patents, and had three technologies officially recognized by the NMPA as Key Core Technologies in China's Medical Device Industry. We have also established close collaborations with top-tier hospitals across China, enabling the large-scale clinical validation of our AI technologies. Our products are now deployed in over 4,000 clinical sites, improving diagnostic efficiency and patient outcomes at scale.

My research interests lie at the intersection of deep learning and medical imaging, bridging deep learning methodologies with real-world clinical applications. Recently, I have been working on designing efficient algorithms for medical multimodal foundation models, aiming to advance intelligent diagnostic systems and enhance clinical decision support. I also maintain a close collaboration with Prof. Liwei Wang.

I obtained my Master's degree from School of EECS, Peking University, advised by Prof. Jufu Feng in 2019, and my Bachelor's degree from Xidian University in 2016.

I am always open to collaborations and academic or industrial partnerships in the areas of medical AI, intelligent diagnostics, and foundation models. If you are interested in potential collaboration or exchange, please feel free to contact me.

Email / Google Scholar

Selected Publications & Preprints

See full list on Google Scholar and my citation map.

	DeformCL: Learning Deformable Centerline Representation for Vessel Extraction in 3D Medical Image Ziwei Zhao, Zhixing Zhang, Yuhang Liu†, Zhao Zhang, Haojun Yu, Dong Wang, Liwei Wang (* denotes equal contribution, † denotes project lead) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 paper / code
	Learning Disentangled Representation for Vessel-specific Coronary Artery Calcium Scoring Junjie Hou, Nianxi Liao, Jia Liu, Yuhang Liu†, Jianxing Qiu† († denotes corresponding author) IEEE International Symposium on Biomedical Imaging (ISBI), 2024, (Oral Presentation) paper
	Topology-Preserving Automatic Labeling of Coronary Arteries via Anatomy-aware Connection Classifier Zhixing Zhang, Ziwei Zhao Dong Wang, Shishuang Zhao, Yuhang Liu, Jia Liu, Liwei Wang International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), 2023 paper / code
	PointScatter: Point Set Representation for Tubular Structure Extraction Dong Wang, Zhao Zhang, Ziwei Zhao Yuhang Liu, Yihong Chen Liwei Wang European Conference on Computer Vision (ECCV), 2022, (Oral Presentation) paper / code
	Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection Yuhang Liu, Fandong Zhang, Chaoqi Chen, Siwen Wang, Yizhou Wang, Yizhou Yu IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021, paper
	Cross-view Correspondence Reasoning based on Bipartite Graph Convolutional Network for Mammogram Mass Detection Yuhang Liu, Fandong Zhang, Qianyi Zhang, Siwen Wang, Yizhou Wang, Yizhou Yu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, (Oral Presentation) paper
	FingerNet: An Unifified Deep Network for Fingerprint Minutiae Extraction Yao Tang, Fei Gao, Jufu Feng, Yuhang Liu International Joint Conference on Biometrics (IJCB), 2017 (Oral Presentation) paper / code

Selected Awards

ACM-ICPC Asia Regional, Silver Medal 2014

Academic Services

Journal Reviewer: TPAMI

Conference Reviewer: ICCV, ECCV, MICCAI

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