Zhe (Jack) Xu

Ph.D. Candidate

The Chinese University of Hong Kong
Hong Kong, China

Email: jackxz [at] link.cuhk.edu.hk

@Boston, 🇺🇸

Biography

I am a year-3 Ph.D. candidate at The Chinese University of Hong Kong, supervised by Prof. Raymond Tong (AIMBE Fellow), supported by Hong Kong PhD Fellowship (HKPFS). I will be joining Massachusetts General Hospital, Harvard Medical School in 2023 fall, hosted 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, supervised by Prof. Jayender Jagadeesan, working closely with Prof. Sandy Wells and Dr. Jie Luo), and B.Eng in Electronic Engineering and B.Sc in Management from UESTC in 2018. I also work closely with Tencent Jarvis Lab led by Dr. Yefeng Zheng (IEEE Fellow) since 2020.

My research lies at advancing medical image analysis with AI, with recent focus on learning under various imperfect data scenarios (e.g., label/data scarcity, noise and heterogeneity) & multimodal data to achieve affordable-yet-accurate medical decision-making. Clinically practical, safe, interpretable, simple-yet-effective methods are favored.

News

[07/2023] Glad to receive MICCAI STAR Award (aka. Travel Award)!
[06/2023] MTCL is selected as part of tutorial in DLMA‘23 summer camp of TUM (hosted by Prof. Nassir Navab)!
[06/2023] Our AC-MT for SSL was accepted by Medical Image Analysis (IF=10.9)!
[06/2023] 4 papers on label-efficient/multimodal learning accepted by MICCAI 2023 (2 early accept(14%), 1 oral(3%))!
[05/2023] 1 mentoring paper on SFUDA was accepted by Computers in Biology and Medicine (IF=7.7)!
[03/2023] 1 paper on SSL accepted by EMBC 2023 (oral)!
[02/2023] ProtoSeg on active histopathology analysis was accepted by IPMI 2023 (oral)! Congrats to Jiangpeng,Wentao!
[10/2022] 1 joint paper Learn2Reg on DL-oriented multi-task image registration benchmark was accepted by IEEE TMI!
[09/2022] Attending MICCAI’22 in Singapore! Welcome to catch up:)
[07/2022] Passed the qualified exam towards a PhD candidate!
[06/2022] 2 joint papers on image registration and landmark error screening were accepted by MICCAI 2022 (~31%)!
[05/2022] Awarded Talent Development Scholarship on Innovation, science and technology from HK Gov!
[05/2022] Our MTCL for learning segmentation with noisy labels was accepted by IEEE TMI (IF=11.037)!
[05/2022] 2 papers on image registration and SFUDA early accepted by MICCAI 2022 (Top 13%)!
[03/2022] Our CPCL, a supervised-like semi-supervised segmentation, was accepted by IEEE J-BHI!
[01/2022] 1 paper on cross-domain few-shot learning accepted by ICASSP 2022. Congrats to Yixin!
[09/2021] Invited to give oral presentation at MICCAI Learn2Reg and contribute to the Challenge paper.
[06/2021] Awarded as Outstanding Graduate of Beijing; Thank you, THU and Harvard! Moving to Hong Kong!
[05/2021] 2 papers on noisy-label segmentation and WSI segmentation early accepted by MICCAI 2021 (Top 13%)!
[04/2021] Glad to be Hong Kong PhD Fellowship (HKPFS) Awardee
[01/2021] 3 papers on image registration accepted by ISBI 2021, ICASSP 2021, and IJCARS
[10/2020] Awarded National Scholarship (for postgraduate) at Tsinghua
[06/2020] 1 paper on synthesis-based multimodal registration accepted by MICCAI 2020!
[09/2019] Moved to Boston, USA and joined SPL of Harvard
[06/2019] Our startup "CloudSpace: AI+design" won a Gold Award in the Greater Bay Area Entrepreneurship Competition

Selected Publications | Full List

*/Journal/*
	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]
	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/*
	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(in press), 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]
	Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation Jiangpeng Yan, Hanbo Chen, Kang Wang, Yan Ji, Yuyao Zhu, Jingjing Li, Dong Xie, Zhe Xu, Junzhou Huang, Shuqun Cheng, Xiu Li, Jianhua Yao. Medical Image Computing and Computer Assisted Interventions (MICCAI), 2021. (early accept) [paper]
	Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance Zhe Xu, Jiangpeng Yan, Jie Luo, Xiu Li, Jayender Jagadeesan. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. [paper]
	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/*
	Trust It or Not: Confidence-Guided Automatic Radiology Report Generation Yixin Wang, Zihao Lin, Zhe Xu, Haoyu Dong, Jiang Tian, Jie Luo, Zhongchao Shi, Yang Zhang, Jianping Fan, Zhiqiang He. (* equal contribution) Under Review, 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 Revision at IEEE Transactions on Medical Imaging. [paper]

Honors & Awards

2023, MICCAI Best Paper and Young Scientist Award Nomination

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

Regular Reviewers/PC Member:
Computer Vision and Pattern Recognition (CVPR)
International Conference on Computer Vision (ICCV)
European Conference on Computer Vision (ECCV)
AAAI Conference on Artificial Intelligence
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
Medical Imaging with Deep Learning (MIDL)
IEEE Transactions on Medical Imaging (TMI)
IEEE Journal of Biomedical and Health Informatics (J-BHI)
Information Fusion
Medical Physics

Teaching

2022-2023

Fall

Big Data in Healthcare (TA, BMEG 3103)

2021-2022

Spring

Big 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, 15+ 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.