😊 About me

Yutong Xie is an Assistant Professor of the Computer Vision Department at MBZUAI. Before joining MBZUAI, she was a Research Fellow at the University of Adelaide (UoA) and a member of the Australian Institute for Machine Learning (AIML).

My research primarily focuses on computer vision and machine learning for healthcare sector, aiming to develop intelligent solutions to assist healthcare professionals in anatomical structure segmentation, disease diagnosis, prognosis, and therapy, particularly in the context of medical data analysis with limited annotations. I have published more than 50 peer-reviewed publications, most in flagship journals/conference proceedings including IEEE-TPAMI/TMI/TIP, IJCV, Medical Image Analysis, IEEE-TCSVT, MICCAI, CVPR, ECCV, IJCAI, ACCV.

Research Topics:

• Cutting-edge Technologies:
  • Annotation-efficient deep learning & Self-/Semi-/Weak-supervised learning
  • Multi-modal learning (2D/3D images/text/gene data) & Foundation model
  • Artificial Intelligence Generated Content (AIGC)
  • Image classification/segmentation/detection
• Medical Image Segmentation & Computer-Aided Diagnosis/Prognosis:
  • Chest/Abdomen/Brain/Skin/Gland/Eye/Oral regions
  • X-ray/CT/MRI/Dermoscopy/Pathology/Fundus/Report/Clinical/Gene data

[Note]: I am actively seeking highly motivated PhD students, Master’s students, and interns/visiting students to join my group. If you are interested in working with me on the topics mentioned above, please feel free to contact me via email and refer to this link for further information.

🔥 News

• 2025.01: 🎉🎉🎉 Our survey paper on Advances in Attention Mechanisms for Medical Image Segmentation is accepted by Computer Science Review(IF=13.3)!
  
• 2024.12: 🎉🎉🎉 Our paper on Semi-supervised Medical Image Segmentation is accepted by IJCV(IF=11.6)!
  
• 2024.11: 🎉🎉🎉 Our survey paper on Medical Vision-and-Language Applications and Their Techniques is available here!
  
• 2024.10: 🎉🎉🎉 Our paper on Learning with Label Noise is accepted by IJCV(IF=11.6)! Paper is available here
  
• 2024.09: 🎉🎉🎉 Our paper on Radiology Report Generation across Anatomical Regions is accepted by ACCV 2024 (Oral)!
  
• 2024.09: 🎉🎉🎉 I am very privileged to be selected as one of World’s Top 2% Scientists 2024 in Standford and Elsevier’s report!
  
• 2024.08: 🎉🎉🎉 Our paper on Multi-modal Multi-label Skin Lesion Classification is accepted by WACV 2024!
  
• 2024.08: 🎉🎉🎉 Our MICCAI 2023 extension paper – MedIM is accepted by Medical Image Analysis(IF=10.7)!
  
• 2024.07: 🎉🎉🎉 Our ECCV 2022 extension paper – UniMiSS+ is accepted by IEEE-TPAMI(IF=20.8)!
  
• 2024.07: 🎉🎉🎉 Our TransUNet paper is accepted by Medical Image Analysis(IF=10.7)!
  
• 2024.07: 🎉🎉🎉 Our paper on Semi-supervised Medical Image Segmentation is accepted by IEEE-TMI(IF=8.9)!
  
• 2024.06: 🎉🎉🎉 Four papers are accepted by MICCAI 2024! (Three of them are early accepted)
  
• 2024.05: We are organizing the ACM MM 2024 challenge on Multi-rater Medical Image Segmentation for Radiotherapy Planning
  
• 2024.04: We are organizing the MICCAI 2024 challenge on Multi-class Brain Hemorrhage Segmentation in Non-contrast CT
  
• 2024.04: 🎉🎉🎉 I am very pleased to receive the CVPR DEI Grant to attend CVPR 2024.
  
• 2024.03: 🎉🎉🎉 I will serve as an Area Chair at MICCAI 2024!
  
• 2024.02: 🎉🎉🎉 Four papers on medical vision-language learning, continual self-supervised learning, and DNN Interpretation are accepted by CVPR 2024!

📝 Publications

$\dagger$: equal contributions; $\ast$: corresponding author

Journal (Selective)

• UniMiSS+: Universal Medical Self-Supervised Learning From Cross-Dimensional Unpaired Data, Yutong Xie, Jianpeng Zhang, Yong Xia, Qi Wu^$\ast$. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI). (Impact factor=20.8) Code

• Consistency-guided Differential Decoding for Enhancing Semi-supervised Medical Image Segmentation, Qingjie Zeng^$\dagger$, Yutong Xie^$\dagger$, Zilin Lu, Mengkang Lu, Jingfeng Zhang, and Yong Xia^$\ast$. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9) Code

• ReFs: A Hybrid Pre-training Paradigm for 3D Medical Image Segmentation, Yutong Xie, Jianpeng Zhang, Lingqiao Liu, Hu Wang, Yiwen Ye, Johan Verjans, Yong Xia^$\ast$. Medical Image Analysis. (Impact factor=10.7)

• Learning from Partially Labelled Data for Multi-organ and Tumor Segmentation, Yutong Xie, Jianpeng Zhang, Yong Xia^$\ast$, and Chunhua Shen^$\ast$. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI). (Impact factor=20.8) Code

• Modeling Annotator Preference and Stochastic Annotation Error for Medical Image Segmentation, Zehui Liao, Shishuai Hu, Yutong Xie, and Yong Xia^$\ast$. Medical Image Analysis. (Impact factor=10.7) Code

• Learning from Ambiguous Labels for Lung Nodule Malignancy Prediction, Zehui Liao^$\dagger$, Yutong Xie^$\dagger$, Shishuai Hu, and Yong Xia^$\ast$. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9)

• Intra- and Inter-pair Consistency for Semi-supervised Gland Segmentation, Yutong Xie, Jianpeng Zhang, Zhibin Liao, Johan Verjans, Chunhua Shen, and Yong Xia^$\ast$. IEEE Transactions on Image Processing (IEEE-TIP). (Impact factor=10.8)

• Viral Pneumonia Screening on Chest X-rays Using Confidence-Aware Anomaly Detection, Jianpeng Zhang^$\dagger$, Yutong Xie^$\dagger$, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen^$\ast$, and Yong Xia^$\ast$. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9) (ESI Highly Cited Paper)

• SESV: Accurate Medical Image Segmentation by Predicting and Correcting Errors, Yutong Xie^$\dagger$, Jianpeng Zhang^$\dagger$, Hao Lu, Chunhua Shen, and Yong Xia^$\ast$. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9)

• Inter-slice Context Residual Learning for 3D Medical Image Segmentation, Jianpeng Zhang, Yutong Xie, Yan Wang, and Yong Xia^$\ast$. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9) Code

• A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification, Yutong Xie^$\dagger$, Jianpeng Zhang^$\dagger$, Yong Xia^$\ast$, and Chunhua Shen. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9) Code (ESI Highly Cited Paper)

• Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT, Yutong Xie, Yong Xia^$\ast$, Jianpeng Zhang, Yang Song, David Dagan Feng, Michael Fulham, and Weidong Cai. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9). Code (ESI Highly Cited Paper)

• Attention Residual Learning for Skin Lesion Classification, Jianpeng Zhang, Yutong Xie, Yong Xia^$\ast$, and Chunhua Shen. IEEE Transactions on Medical Imaging (IEEE-TMI). (Impact factor=8.9). (ESI Highly Cited Paper)

• Semi-supervised Adversarial Model for Benign-Malignant Lung Nodule Classification on Chest CT, Yutong Xie, Jianpeng Zhang, and Yong Xia^$\ast$. Medical Image Analysis. (Impact factor=10.7)

• Medical Image Classification Using Synergic Deep Learning, Jianpeng Zhang, Yutong Xie, Qi Wu, and Yong Xia^$\ast$. Medical Image Analysis. (Impact factor=10.7)

• Fusing Texture, Shape and Deep Model-learned Information at Decision Level for Automated Classification of Lung Nodules on Chest CT, Yutong Xie, Jianpeng Zhang, Yong Xia^$\ast$, Fulham Michael, and Yanning Zhang. Information Fusion. (Impact factor=14.7) *(Third prize of the 14th Excellent Academic Paper of Natural Science of Shaanxi Province, China)

• Classification of Medical Images in Biomedical Literature by Jointly Using Deep and Handcrafted Visual Features, Jianpeng Zhang, Yong Xia^$\ast$, Yutong Xie, Michael Fulham, and David Dagan Feng. IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI). (Impact factor=6.7)

Conference (Selective)

• Act Like a Radiologist: Radiology Report Generation across Anatomical Regions, Qi Chen^$\dagger$, Yutong Xie^$\dagger$, Biao Wu, Xiaomin Chen, James Ang, Minh-Son To, Xiaojun Chang, and Qi Wu^$\ast$. Code (Oral, 17.4% of accepted papers, 5.6% of submitted papers)

• Spot the Difference: Difference Visual Question Answering with Residual Alignment, Zilin Lu^$\dagger$, Yutong Xie^$\dagger$, Qingjie Zeng, Mengkang Lu, Qi Wu, and Yong Xia^$\ast$. Code (Early Accept)

• Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis, Vu Minh Hieu Phan, Yutong Xie, Bowen Zhang, Yuankai Qi, Zhibin Liao, Antonios Perperidis, Son Lam Phung, Johan W. Verjans, and Minh-Son To. Code (Early Accept)

• Reciprocal Collaboration for Semi-supervised Medical Image Classification, Qingjie Zeng, Zilin Lu, Yutong Xie, Mengkang Lu, Xinke Ma, and Yong Xia^$\ast$. (Early Accept)

• AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis, Townim F. Chowdhury, Vu Minh Hieu Phan, Kewen Liao, Minh-Son To, Yutong Xie, Anton van den Hengel, Johan W. Verjans, and Zhibin Liao^$\ast$. Code

• PairAug: What Can Augmented Image-Text Pairs Do for Radiology?, Yutong Xie^$\dagger$, Qi Chen^$\dagger$, Sinuo Wang, Minh-Son To, Iris Lee, Ee Win Khoo, Kerolos Hendy, Daniel Koh, Yong Xia, and Qi Wu^$\ast$. Code

• Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning, Yiwen Ye, Yutong Xie^$\ast$, Jianpeng Zhang, Ziyang Chen, Qi Wu, and Yong Xia^$\ast$. Code (Highlights, 11.9% of accepted papers, 2.8% of submitted papers)

• Decomposing Disease Descriptions for Enhanced Pathology Detection: A Multi-Aspect Vision-Language Matching Framework, Minh Hieu Phan, Yutong Xie, Yuankai Qi, Lingqiao Liu, Liyang Liu, Bowen Zhang, Zhibin Liao, Qi Wu, Minh-Son To, Johan W. Verjans. Code

• CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation, Townim Faisal Chowdhury, Kewen Liao, Vu Minh Hieu Phan, Minh-Son To, Yutong Xie, Kevin Hung, David Ross, Anton van den Hengel, Johan W. Verjans, Zhibin Liao^$\ast$. Code

• PEFAT: Boosting Semi-supervised Medical Image Classification via Pseudo-loss Estimation and Feature Adversarial Training, Qingjie Zeng^$\dagger$, Yutong Xie^$\dagger$, Zilin Lu, and Yong Xia^$\ast$. Code (Highlights, 10% of accepted papers, 2.6% of submitted papers)

• MedIM: Boost Medical Image Representation via Radiology Report-guided Masking, Yutong Xie, Lin Gu, Tatsuya Harada, Jianpeng Zhang, Yong Xia, and Qi Wu^$\ast$. Code

• Unpaired Cross-modal Interaction Learning for COVID-19 Segmentation on Limited CT Images, Qingbiao Guan^$\dagger$, Yutong Xie^$\dagger$, Bing Yang, Jianpeng Zhang, Zhibin Liao, Qi Wu, and Yong Xia^$\ast$. Code

• Improved Flexibility and Interpretability of Large Vessel Stroke Prognostication using Image Synthesis and Multi-task Learning, Minyan Zeng, Yutong Xie, Minh-Son To, Lauren Oakden-Rayner, Luke Whitbread, Stephen Bacchi, Alix Bird, Luke Smith, Rebecca Scroop, Timothy Kleinig, Jim Jannes, Lyle J Palmer, and Mark Jenkinson.

• UniSeg: A Prompt-Driven Universal Segmentation Model as Well as A Strong Representation Learner, Yiwen Ye^$\dagger$, Yutong Xie^$\dagger$, Jianpeng Zhang, Ziyang Chen, and Yong Xia^$\ast$. Code (Early Accept)

• TPRO: Text-prompting-based Weakly Supervised Histopathology Tissue Segmentation, Shaoteng Zhang, Jianpeng Zhang, Yutong Xie^$\ast$, and Yong Xia^$\ast$. Code (Early Accept)

• Transformer-based Annotation Bias-aware Medical Image Segmentation, Zehui Liao, Shishuai Hu, Yutong Xie^$\ast$, and Yong Xia^$\ast$. Code (Early Accept)

• UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality Barrier, Yutong Xie, Jianpeng Zhang, Yong Xia, and Qi Wu^$\ast$. Code

• DoDNet: Learning to Segment Multi-organ and Tumors from Multiple Partially Labeled Datasets, Jianpeng Zhang^$\dagger$, Yutong Xie^$\dagger$, Yong Xia^$\ast$, and Chunhua Shen^$\ast$. Code

• CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation, Yutong Xie^$\dagger$, Jianpeng Zhang^$\dagger$, Chunhua Shen, and Yong Xia^$\ast$. Code (Oral Presentation, Best of MICCAI 2021)

• Pairwise Relation Learning for Semi-supervised Gland Segmentation, Yutong Xie$\dagger$, Jianpeng Zhang$\dagger$, Zhibin Liao, Chunhua Shen, Johan Verjans, and Yong Xia^$\ast$.

• Light-Weight Hybrid Convolutional Network for Liver Tumor Segmentation, Jianpeng Zhang, Yutong Xie, Pingping Zhang, Hao Chen, Yong Xia^$\ast$, and Chunhua Shen.

• Deep Segmentation-Emendation Model for Gland Instance Segmentation, Yutong Xie, Hao Lu, Jianpeng Zhang, Chunhua Shen, and Yong Xia^$\ast$. (Early Accept)

• Skin Lesion Classification in Dermoscopy Images using Synergic Deep Learning, Jianpeng Zhang, Yutong Xie, Qi Wu, and Yong Xia^$\ast$.

• Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT, Yutong Xie, Yong Xia^$\ast$, Jianpeng Zhang, David Dagan Feng, Michael Fulham, and Weidong Cai.

💻 Services

Conference Area Chair:

MICCAI 2023; MICCAI 2024.

Program Committee Member:

ICML 2025, MIDL 2025, ICLR 2024, NeurIPS 2023, CVPR 2022/2023/2024, ICCV 2021/2023, ECCV 2022/2024, AAAI 2020-2024, MICCAI 2019-2022, PRCV 2020, DICTA 2020, etc.

Journal Reviews:

• Transactions on Pattern Analysis and Machine Intelligence
• IEEE Transactions on Medical Imaging
• Medical Image Analysis
• IEEE Transactions on Artificial Intelligence
• IEEE Transactions on Circuits and Systems for Video Technology
• IEEE Journal of Biomedical and Health Informatics
• Scientific Reports
• Pattern Recognition
• etc

Challenges Organization :

• MBH-Seg@MICCAI2024 challenge, MBH-Seg: Multi-class Brain Hemorrhage Segmentation in Non-contrast CT. Data: 6 Oct 2024, Venue: MICCAI 2024

  Main Organizers: Yutong Xie, Minh-Son To, Chenyu Wang, Dongang Wang

• MMIS-2024 challenge, A New Benchmark for Multi-rater Medical Image Segmentation in Radiotherapy Planning of Nasopharyngeal Carcinoma. Data: 28 Oct 2024, Venue: ACM MM 2024

  Main Organizers: Yicheng Wu, Yutong Xie, Xiangde Luo, Wenjun Liao, Minh-Son To, Qi Wu, Jianfei Cai

🎖 Honors and Awards

• 2024, Top 2% Scientists Worldwide, Stanford University
• 2024, CVPR 2024 DEI travel grants
• 2023, CSIG Doctoral Dissertation Award (only 10 scholars selected from China)
• 2023, Top 2% Scientists Worldwide, Stanford University
• 2023, Distinguished Reviewer of IEEE-TMI
• 2023, Outstanding Reviewer of CVPR 2023
• 2022, Top 2% Scientists Worldwide, Stanford University
• 2022, Distinguished Reviewer of IEEE-TMI
• 2020-2021, Innovation Foundation for Doctor Dissertation (about 12,000$$$)(PI).
• 2020, Second prize of ISICDM 2020 Challenge on Lung Tissue Segmentation.
• 2020, Honorable Mention of MICCAI 2020 MyoPS Challenge
• 2020, Fourth prize of MICCAI 2020 Thyroid Nodule Segmentation Challenge
• 2020, Outstanding Graduate Student Pacesetter
• 2018-2020, National Scholarship (top 1% of students) (annually)
• 2018, Academic Star (top 1% of students)
• 2016-2019, First-class Scholarship for Outstanding Graduate student (annually)