Zhe (Jack) Xu

Ph.D. Candidate

Massachusetts General Hospital, Harvard Medical School &
The Chinese University of Hong Kong
Now: Boston, MA, USA

Email: jackxz [at] link.cuhk.edu.hk; zxu8 [at] bwh.harvard.edu


@Boston, 🇺🇸

Biography

I am a year-3 Ph.D. candidate at The Chinese University of Hong Kong, supervised by Prof. Raymond Tong (AIMBE Fellow). I am also co-trained at CAMCA, Massachusetts General Hospital, Harvard Medical School, supervised by Prof. Quanzheng Li. I obtained my M.S. in Computer Science at Tsinghua University in 2021, supervised by Prof. Xiu Li (joint training at SPL, Brigham and Women's Hospital, Harvard Medical School, working closely with Prof. Jayender Jagadeesan, Prof. Sandy Wells), and B.Eng in Electronic Engineering and B.Sc in Management from UESTC in 2018. I also work closely with Tencent Youtu Jarvis Center led by Dr. Yefeng Zheng (IEEE Fellow) since 2020. I'm a recipient of the Hong Kong PhD Fellowship (HKPFS).

My research lies at advancing medical image analysis with AI to achieve affordable-yet-accurate medical decision-making, with recent focus on 1) learning under various imperfect data scenarios (e.g., label/data scarcity, noise and heterogeneity), 2) multimodal data supported representation learning and decision making, 3) data-centric, human-in-the-loop, continual learning for generalizable real-world agents, 4) generative AI for brain decoding and medical data enhancement.

News

Selected Publications | Full List

                                                                  
/*Journal*/

Separated Collaborative Learning for Semi-supervised Prostate Segmentation with Multi-site Heterogeneous Unlabeled MRI Data

Zhe Xu, Donghuan Lu, Jie Luo, Yefeng Zheng, Raymond Tong

Medical Image Analysis (MedIA), 2024.

(IF: 10.9, JCR-Q1)

[paper]

Ambiguity-selective Consistency Regularization for Mean-Teacher Semi-supervised Medical Image Segmentation

Zhe Xu, Yixin Wang, Donghuan Lu, Xiangde Luo, Jiangpeng Yan, Yefeng Zheng, Raymond Tong

Medical Image Analysis (MedIA), 2023.

(IF: 10.9, JCR-Q1)

[paper, code]

Anti-interference from Noisy Labels: Mean-Teacher-assisted Confident Learning for Medical Image Segmentation

Zhe Xu, Donghuan Lu, Jie Luo, Yixin Wang, Jiangpeng Yan, Kai Ma, Yefeng Zheng, Raymond Tong

IEEE Transactions on Medical Imaging (TMI), 2022.

(IF: 11.037, JCR-Q1)

[paper, code]

All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation

Zhe Xu, Yixin Wang, Donghuan Lu, Lequan Yu, Jiangpeng Yan, Jie Luo, Kai Ma, Yefeng Zheng, Raymond Kai-yu Tong

IEEE Journal of Biomedical and Health Informatics (J-BHI), 2022.

(IF: 7.021, JCR-Q1)

[paper, code]

Trust It or Not: Confidence-Guided Automatic Radiology Report Generation

Yixin Wang*, Zihao Lin*, Zhe Xu, Haoyu Dong, Jiang Tian, Jie Luo, Zhongchao Shi, Lifu Huang, Yang Zhang, Jianping Fan, Zhiqiang He. (* equal contribution)

Neurocomputing, 2024.

(IF: 6.0, JCR-Q1)

[paper]

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

Wentao Pan, Zhe Xu (ADLReg | THU Team)

Full Author List: Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Jens Sjölund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich

IEEE Transactions on Medical Imaging (TMI), 2022.

(IF: 11.037, JCR-Q1)

[paper, page, our code]
/*Conference*/

Diversified and Personalized Multi-rater Medical Image Segmentation

Yicheng Wu*, Xiangde Luo*, Zhe Xu, Xiaoqing Guo, Lie Ju, Zongyuan Ge, Wenjun Liao, and Jianfei Cai

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

(Highlight)

[paper, code]

Category-Level Regularized Unlabeled-to-Labeled Learning for Semi-supervised Prostate Segmentation with Multi-site Unlabeled Data

Zhe Xu, Donghuan Lu, Jiangpeng Yan, Jinghan Sun, Jie Luo, Dong Wei, Sarah Frisken, Quanzheng Li, Yefeng Zheng, Raymond Tong

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2023.

(Oral, early accept)

[paper]

Towards Expert-Amateur Collaboration: Prototypical Label Isolation Learning for Left Atrium Segmentation with Mixed-Quality Labels

Zhe Xu, Jiangpeng Yan, Donghuan Lu, Yixin Wang, Jie Luo, Yefeng Zheng, Raymond Tong

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2023.
[paper, code]

You've Got Two Teachers: Co-evolutionary Image and Report Distillation for Semi-supervised Anatomical Abnormality Detection in Chest X-ray

Jinghan Sun*, Dong Wei*, Zhe Xu, Donghuan Lu, Hong Liu, Liansheng Wang, Yefeng Zheng (* equal contribution)

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2023.

(early accept)

[paper, code]

Weakly Supervised Medical Image Segmentation via Superpixel-guided Scribble Walking and Class-wise Contrastive Regularization

Meng Zhou*, Zhe Xu*^, Kang Zhou, Raymond Tong^ (^corresponding)

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2023.
[paper, code]

Human-machine Interactive Tissue Prototype Learning for Label-efficient Histopathology Image Segmentation

Wentao Pan*, Jiangpeng Yan*, Hanbo Chen*, Jiawei Yang, Zhe Xu, Xiu Li, Jianhua Yao (* equal contribution)

Information Processing in Medical Imaging (IPMI), 2023.

(Oral)

[paper, code]

Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration

Zhe Xu, Jie Luo, Donghuan Lu, Jiangpeng Yan, Sarah Frisken, Jayender Jagadeesan, William Wells III, Xiu Li, Yefeng Zheng, Raymond Tong

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022.

(early accept)

[paper]

Denoising for Relaxing: Unsupervised Domain Adaptive Fundus Image Segmentation without Source Data

Zhe Xu, Donghuan Lu, Yixin Wang, Jie Luo, Dong Wei, Yefeng Zheng, Raymond Tong

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022.

(early accept)

[paper][Extended application of our MTCL (MICCAI'21)]

Noisy Labels are Treasure: Mean-Teacher-assisted Confident Learning for Hepatic Vessel Segmentation

Zhe Xu, Donghuan Lu, Yixin Wang, Jie Luo, Jayender Jagadeesan, Kai Ma, Yefeng Zheng, Xiu Li

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2021.

(early accept)

[paper, code][Part of tutorial for DLMA at TUM]

Adversarial Uni-and Multi-modal Stream Networks for Multimodal Image Registration

Zhe Xu, Jie Luo, Jiangpeng Yan, Ritvik Pulya, Xiu Li, William Wells III, Jayender Jagadeesan.

Medical Image Computing and Computer Assisted Interventions (MICCAI), 2020.

(Oral)

[paper] [Nice Follow-up: MedIA@JHU, DDMReg(TMI)@Harvard]
/*Preprint*/

MMedAgent: Learning to Use Medical Tools with Multi-modal Agent

Binxu Li, Tiankai Yan, Yuanting Pan, Zhe Xu, Jie Luo, Ruiyang Ji, Shilong Liu, Haoyu Dong, Zihao Lin, Yixin Wang

Under Review, 2024. [paper, code, Recs.: Autonomous Agents, Tool Learning]

Semi-supervised Semantic Segmentation Meets Masked Modeling: Fine-grained Locality Learning Matters in Consistency Regularization

Weitao Pan, Zhe Xu, Jiangpeng Yan, Zihan Wu, Raymond Tong, Jianhua Yao.

Under Review, 2023. [paper]

Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report Generation

Jinghan Sun*, Dong Wei*, Zhe Xu, Donghuan Lu, Hong Liu, Hong Wang, Liansheng Wang, Yefeng Zheng. (* equal contribution)

Major Revision in IEEE TMI, 2023. [paper]

Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction

Jiangpeng Yan, Chenghui Yu, Hanbo Chen, Zhe Xu, Junzhou Huang, Xiu Li, Jianhua Yao.

Under Review in MedIA, 2023. [paper]

Honors & Awards

2024, Reaching Out Award (HKSAR Gov Fund)
2024, Overseas Research Attachment Programme (CUHK Engineering)
2023, IEEE TMI Distinguished Reviewer (Gold Level)
2023, MICCAI Best Paper and Young Scientist Award Finalist
2023, MICCAI STudent-Author Registration (STAR) Award
2022, Hong Kong,China-Asia-Pacific Economic Cooperation Scholarship (APEC Scholarship.)
2022, Talent Development Scholarship on Innovation, science and technology (HKSAR Gov.)
2021-2025, Hong Kong PhD Fellowship (HKPFS) & CUHK Vice-Chancellor’s Scholarship
2021, Outstanding Graduate of Beijing
2016/2020, China National Scholarship (for undergraduate / postgraduate)
2019, Gold Prize of Guangdong-HK-Macao Greater Bay Area College Social Entrepreneurship Challenge
2017, Silver Award in National Entrepreneurship Competition for college students
2016, First Prize of China Undergraduate Mathematical Contest in Modeling (CUMCM)

Professional Services

Teaching

2022-2023FallBig Data in Healthcare (TA, BMEG 3103) 2021-2022SpringBig Data in Healthcare (TA, BMEG 3103)

Misc.

Curiosity drives my research, also my life. I pursue credo of "Work Smart, Play Hard", where I enjoy traveling (all over China, 20+ countries [Vlogs]), surfskate, snowboard, Frisbee, SCUBA diving (PADI), (wake-)surfing, non-convex gradient ascent (hiking), cocktail and jazz blues. I spent some of my vacations on volunteering, e.g., English teaching in Cambodia and protecting animals in Thailand, Indonesia and Nepal.

© Jack Xu