Yuting He 何宇霆

Research Associate

Rm 517A, Wickenden Bldg,
Case Western Reserve University
Cleveland, OH 44106

Email: yuting [DOT] he4 [AT] case [DOT] edu

Google Scholar Github ResearchGate

If you’re interested in medical image analysis or foundational models, I’d be glad to share insights, provide guidance, or explore research opportunities together. Don’t hesitate to get in touch.

Biography

I am currently a Research Associate in the department of biomedical engineering, Case Western Reserve University, working with Shuo Li. Drawing upon biomedical informatics, computer vision, and deep learning, my research focuses on developing novel methodologies to learn more efficient extraction of knowledge in medical information for computer-aided diagnosis, surgery, and medical imaging. I have published more than 20 peer-reviewed journal/conference articles, including RBME, CVPR, ECCV, TNNLS, MedIA, NC, TIP, J-BHI, IJCAI, MICCAI, IPMI, etc. I was the organizer of the MICCAI-KiPA22 challenge, and provided professional service for J-BHI, TMI, CVPR, ICCV, MICCAI, AAAI, and NeurIPS.

News

[2025.07] 1 paper named Adaptation follow human attention: Gaze-assisted medical segment anything model has been accepted by IEEE TCSVT (IF: 11.1)
[2025.07] 1 paper named Conditional Virtual Imaging for Few-Shot Vascular Image Segmentation has been accepted by IEEE TMI (IF: 9.8)
[2025.06] 1 paper has been accepted by ICCV 2025
[2025.05] 1 paper has been accepted by ICML 2025
[2025.02] 1 paper about Homeomorphism and Medical Image Representation Learning has been accepted by T-PAMI (IF: 20.8)
[2024.11] Our survey on healthcare foundation model has been accepted by IEEE RBME (IF: 17.2)
[2024.10] An imaging foundation model, TAMP, has been released. It can achieve universal enhancement for any non-ideal measurement CT images.
[2024.04] A survey about healthcare foundation models has been released. This survey is "Foundation Model for Advancing Healthcare: Challenges, Opportunities and Future Directions"
[2023.12] I have graduated from Southeast University! My PhD thesis is "Data-Efficient Learning Algorithm in Medical Image Segmentation" (in Chinese)
[2023.12] 1 paper has been accepted by J-BHI 2023
[2023.11] I achieved the Bao Gang Outstanding Student Award which is one of the top educational scholarships in China (Only 500 students in China each year)
[2023.11] Our paper "Segment Anything in Medical Images" has been formally accepted by Nature Communications (Impact Factor: 17.0) [code]
[2023.09] 1 paper has been accepted by ICCV 2023
[2023.06] 2 papers have been accepted by MICCAI 2023
[2023.02] 1 paper has been accepted by CVPR 2023
[2023.02] 1 paper has been accepted by JBHI
[2023.02] 1 paper has been accepted by KBS
[2022.08] 1 paper has been accepted by TNNLS
[2022.06] MICCAI 2022 KiPA challenge is in full swing
[2022.06] 4 papers are accepted by MICCAI 2022
[2022.05] 1 paper has been accepted by IJCAI
[2021.10] 1 paper has been accepted by TIP

Awards and Honors

2023, Bao Gang Outstanding Student Award (宝钢优秀学生奖, 500 students in China each year)
2021, 2023, National Scholarship
2023, Merit student of Jiangsu Province
2022, Southeast University Good Youth Award (东大好青年, 10 students in SEU each year)
2022, Southeast University Graduate Student of the Year (正·青年, 10 graduated students in SEU each year)
2019-2021, Merit student of Southeast University
2020, Southeast University Doctoral Freshman Award

Selected Publications [Google Scholar]

☆ Foundation and Pre-training Models for Biomedical Data

Vector Contrastive Learning For Pixel-Wise Pretraining In Medical Vision.

Yuting He, Shuo Li
IEEE/CVF International Conference on Computer Vision
ICCV 2025 | Paper | Code | Slide | 中文解读

Adaptation follow human attention: Gaze-assisted medical segment anything model.

Rongjun Ge, Ruiyi Li, Chong Wang, Yuxin Liu, Heng Zhu, Jean-Louis Coatrieux, Daoqiang Zhang, Jian Lu, Yang Chen, Shuo Li, Yuting He
IEEE Transactions on Circuits and Systems for Video Technology
IEEE T-CSVT 2025 | Paper | Code

Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learning.

Yuting He, Boyu Wang, Rongjun Ge, Yang Chen, Guanyu Yang, Shuo Li
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE T-PAMI 2025 | Paper | Code | 中文解读

Imaging foundation model for universal enhancement of non-ideal measurement CT.

Foundation Model for Advancing Healthcare: Challenges, Opportunities and Future Directions.

Yuting He, Fuxiang Huang, Xinrui Jiang, Yuxiang Nie, Minghao Wang, Jiguang Wang, Hao Chen.
IEEE Reviews in Biomedical Engineering
IEEE R-BME 2024 | Paper | Awesome repository | Bibtex | 中译版

Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training.

Segment Anything in Medical Images.

Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, Bo Wang.
Nature Communication [In Press]
Nat. Comm 2023 | Paper | Code

☆ Representation- and Annotation-Efficient Biomedical Image Analysis

Conditional Virtual Imaging for Few-Shot Vascular Image Segmentation.

Yanglong He, Rongjun Ge, Hui Tang, Yuxin Liu, Mengqing Su, Jean-Louis Coatrieux, Huazhong Shu, Yang Chen, Yuting He
IEEE Transactions on Medical Imaging
IEEE T-MI 2025 | Paper | Code

Learning Better Registration to Learn Better Few-Shot Medical Image Segmentation: Authenticity, Diversity, and Robustness.

Few-shot Learning for Deformable Medical Image Registration with Perception-Correspondence Decoupling and Reverse Teaching.

Deep complementary joint model for complex scene registration and few-shot segmentation on medical images.

Yuting He, Tiantian Li, Guanyu Yang, Youyong Kong, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Jean-Louis Dillenseger, Shuo Li.
European Conference on Computer Vision
ECCV 2020 | Paper |Code | Slide | Bibtex

Thin Semantics Enhancement via High-Frequency Priori Rule for Thin Structures Segmentation.

Yuting He, Rongjun Ge, Jiasong Wu, Jean-Louis Coatrieux, Huazhong Shu, Yang Chen, Guanyu Yang, Shuo Li.
IEEE International Conference on Data Mining
ICDM 2021 | Paper |Code | Bibtex

XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention.

Jiacheng Shi, Yuting He, Youyong Kong, Jean-Louis Coatrieux, Huazhong Shu, Guanyu Yang, Shuo Li.
International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI 2022 | Paper | Code | Bibtex

MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation.

Zhangfu Dong, Yuting He, Xiaoming Qi, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Guanyu Yang, Shuo Li.
International Joint Conference on Artificial Intelligence
IJCAI 2022 | Paper | Code

☆ AI-assisted Surgery/Diagnosis/Prognosis

Meta grayscale adaptive network for 3D integrated renal structures segmentation.

Yuting He, Guanyu Yang, Jian Yang, Rongjun Ge, Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Huazhong Shu, Jean-Louis Dillenseger, Jean-Louis Coatrieux, Shuo Li.
Medical Image Analysis
MedIA 2021 | Paper | Data (KiPA22 Challenge) | Bibtex

Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.

Multi-Task Learning for Pulmonary Arterial Hypertension Prognosis Prediction via Memory Drift and Prior Prompt Learning on 3D Chest CT.

Guanyu Yang#, Yuting He# (Equal contribution), Yang Lv, Yang Chen, Jean-Louis Coatrieux, Xiaoxuan Sun, Qiang Wang, Yongyue Wei, Shuo Li, and Yinsu Zhu.
IEEE Journal of Biomedical and Health Informatics
IEEE J-BHI 2023 | Paper | Code | Slide (Chinese) | Bibtex

EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation.

Yuting He, Rongjun Ge, Xiaoming Qi, Guanyu Yang, Yang Chen, Youyong Kong, Huazhong Shu, Jean-Louis Coatrieux, Shuo Li.
International Conference on Information Processing in Medical Imaging
IPMI 2021 | Paper | Poster | Bibtex

CPNet: cycle prototype network for weakly-supervised 3D renal compartments segmentation on CT images.

Song Wang#, Yuting He# (Equal contribution), Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Jean-Louis Dillenseger, Jean-Louis Coatrieux, Shuo Li, Guanyu Yang.
International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI 2021 | Paper | Bibtex

Services

Workshop/Challenge Organizers:

Co-organizer of MICCAI-KiPA22 challenge.

Conference Reviewer:

MICCAI, AAAI, CVPR, ICCV, NeurIPS.

Journal Reviewer:

IEEE Transactions on Medical Imaging (TMI)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
IEEE Journal of Biomedical and Health Informatics (J-BHI)
Computerized Medical Imaging and Graphics (CMIG)
Machine Intelligence Research (MIR)