Xiaohan XING

邢小涵

Postdoc Fellow

Department of Radiation Oncology,
Stanford University,
CA, US.

Email: xhxing AT stanford.edu

I am currently a Postdoc Fellow in the Department of Radiation Oncology of Stanford University, advised by Prof. Lei Xing. Before joining Stanford, I worked as a Postdoc Fellow in the Department of Electrical Engineering of City University of Hong Kong, advised by Prof. Yixuan Yuan. I obtained the Ph.D. degree in the Department of Electronic Engineering, The Chinese University of Hong Kong in 2021, supervised by Prof. Max Q.-H. Meng and Prof. Hongsheng Li. Prior to that, I received the B.S. degree in Biomedical Engineering, Shandong University in 2017.

My research interests include Deep Learning, Medical Image Analysis, and Omics Analysis.

I am looking for remote collaborators, please drop me an email if you are interested.

News

[Jun 2024] One paper accepted by MICCAI 2024, congrats to Qi Chen!
[Jun 2024] One abstract accepted by ASTRO 2024, Best of Physics (5/1650)!
[May 2024] Two abstracts accepted by AAPM 2024, both are oral presentation!
[Feb 2024] Excited to be invited to serve as an Area Chair for MICCAI 2024!
[Oct 2023] One paper accepted by Medical Image Analysis 2023.
[Jun 2023] One paper accepted by MICCAI 2023.
[Jun 2023] One paper accepted by Medical Image Analysis.
[Mar 2023] Join Stanford University to work as a Postdoctoral research fellow.
[Sep 2022] Honored to win the MICCAI society Young Scientist Award 2022!
[May 2022] Two papers early accepted by MICCAI
[Feb 2022] One paper accepted by Bioinformatics
[Dec 2021] One paper accepted by BIBM
[June 2021] Pass Ph.D. thesis defense

Selected Publications

Journal Papers

Comprehensive Learning and Adaptive Teaching: Distilling Multi-Modal Knowledge for Pathological Glioma Grading [paper] [code]
Xiaohan Xing, Meilu Zhu, Zhen Chen, and Yixuan Yuan.
Medical Image Analysis, 2023.
Gradient modulated contrastive distillation of low-rank multi-modal knowledge for disease diagnosis [paper] [code]
Xiaohan Xing, Zhen Chen, Yuenan Hou, and Yixuan Yuan.
Medical Image Analysis, 2023.
Multi-Level Attention Graph Neural Network Based on Co-expression Gene Modules for Disease Diagnosis and Prognosis [paper] [code]
Xiaohan Xing, Fan Yang, Hang Li, Jun Zhang, Yu Zhao, Junzhou Huang, and Jianhua Yao.
Bioinformatics, 2022.
Zoom in Lesions for Better Diagnosis: Attention Guided Deformation Network for WCE Image Classification [paper] [code]
Xiaohan Xing, Yixuan Yuan, Max Q.-H. Meng.
IEEE Transactions on Medical Imaging (TMI), 2020.
Wireless Capsule Endoscopy: A New Tool for Cancer Screening in the Colon with Deep Learning-Based Polyp Recognition [paper]
Xiao Jia*, Xiaohan Xing*, Yixuan Yuan*, Lei Xing, Max Q.-H. Meng.
Proceedings of the IEEE, 2019. (* indicates equal contribution)
Medical federated learning with joint graph purification for noisy label learning
Zhen Chen, Wuyang Li, Xiaohan Xing, Yixuan Yuan.
Medical Image Analysis, 2023.
Boundary-enhanced semi-supervised retinal layer segmentation in optical coherence tomography images using fewer labels
Ye Lu, Yutian Shen, Xiaohan Xing, Chengwei Ye, Max Q.-H. Meng.
Computerized Medical Imaging and Graphics, 2023.
Preoperative prediction of lymph node metastasis in colorectal cancer with deep learning
Hailing Liu, Yu Zhao, Fan Yang, Xiaoying Lou, Feng Wu, Hang Li, Xiaohan Xing, Tingying Peng, Bjoern Menze, Junzhou Huang, Shujun Zhang, Anjia Han, Jianhua Yao, Xinjuan Fan.
BME Frontiers, 2022.
Automatic polyp recognition in colonoscopy images using deep learning and two-stage pyramidal feature prediction
Xiao Jia, Xiaochun Mai, Yi Cui, Yixuan Yuan, Xiaohan Xing, Hyunseok Seo, Lei Xing, Max Q-H Meng.
IEEE Transactions on Automation Science and Engineering (TASE), 2020.

Conference Papers

Accelerated Multi-Contrast MRI Reconstruction via Frequency and Spatial Mutual Learning
Qi Chen, Xiaohan Xing^, Zhen Chen, Zhiwei Xiong.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2024), MOROCCO. (^Corresponding Author)
Multi-Contrast MRI Acceleration with K-Space Progressive Learning and Image-Space Self-to-Peer Aggregation
Xiaohan Xing, Lequan Yu, Lingting Zhu, Lei Xing, Lianli Liu.
66th Annual Meeting of the American Society of Radiation Oncology (ASTRO 2024), Washington DC, United States. (Best of Physics, 5/1650)
Progressive K-Space Learning For MRI Reconstruction From Noisy And Sparse Acquisitions
Xiaohan Xing, Liang Qiu, Lequan Yu, Lingting Zhu, Lei Xing, Lianli Liu.
66th Annual Meeting & Exhibition of the American Association of Physicists in Medicine (AAPM 2024), LA, United States. (Oral)
Accelerated Multi-Contrast MRI Via A Self-To-Peer Aggregation Network
Xiaohan Xing, Lequan Yu, Lingting Zhu, Lei Xing, Lianli Liu.
66th Annual Meeting & Exhibition of the American Association of Physicists in Medicine (AAPM 2024), LA, United States. (Oral)
Gradient and Feature Conformity-Steered Medical Image Classification with Noisy Labels [paper]
Xiaohan Xing, Zhen Chen, Zhifan Gao, Yixuan Yuan.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2023), Canada.
Discrepancy and Gradient-guided Multi-Modal Knowledge Distillation for Pathological Glioma Grading [paper]
Xiaohan Xing, Zhen Chen, Meilu Zhu, Yuenan Hou, Zhifan Gao, Yixuan Yuan.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2022), Singapore.
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification [paper]
Xiaohan Xing, Yuenan Hou, Hang Li, Yixuan Yuan, Hongsheng Li, Max Q.-H. Meng.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2021).
An Interpretable Multi-Level Enhanced Graph Attention Network for Disease Diagnosis with Gene Expression Data [paper]
Xiaohan Xing, Fan Yang, Hang Li, Jun Zhang, Yu Zhao, Mingxuan Gao, Junzhou Huang, and Jianhua Yao.
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021.
Diagnose like a Clinician: Third-order Attention Guided Lesion Amplification Network for WCE Image Classification [paper]
Xiaohan Xing, Yixuan Yuan, Max Q.-H. Meng.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
A Saliency-Aware Hybrid Dense Network for Bleeding Detection in Wireless Capsule Endoscopy Images [paper]
Xiaohan Xing, Yixuan Yuan, Xiao Jia, Max Q.-H. Meng.
IEEE International Symposium on Biomedical Imaging (ISBI), 2019.
Bleeding Detection in Wireless Capsule Endoscopy Image Video Using Superpixel-Color Histogram and a Subspace KNN Classifier
Xiaohan Xing, Xiao Jia, Max Q.-H. Meng.
IEEE Engineering in Medicine and Biology Society (EMBC), 2018.
Locate before Segment: Topology-guided Retinal Layer Segmentation in Optical Coherence Tomography Images
Ye Lu, Yutian Shen, Xiaohan Xing, Max Q.-H. Meng.
IEEE International Conference on Robotics and Automation (ICRA), 2023.
Discrepancy-based Active Learning for Weakly Supervised Bleeding Segmentation in Wireless Capsule Endoscopy Images
Fan Bai, Xiaohan Xing, Yutian Shen, Han Ma, Max Q.-H. Meng.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2022), Singapore.
Multiple Consistency Supervision based Semi-supervised OCT Segmentation using Very Limited Annotations
Ye Lu, Yutian Shen, Xiaohan Xing, Max Q.-H. Meng.
IEEE International Conference on Robotics and Automation (ICRA), 2022.
Unseen Domain Generalization for Prostate MRI Segmentation via Disentangled Representations
Ye Lu, Xiaohan Xing, Max Q.-H. Meng.
IEEE International Conference on Robotics and Biomimetics (ROBIO), 2021.
Multibranch learning for angiodysplasia segmentation with attention-guided networks and domain adaptation
Xiao Jia, Xiaochun Mai, Xiaohan Xing, Yutian Shen, Jiankun Wang, Max Q.-H. Meng.
IEEE International Conference on Robotics and Automation (ICRA), 2021.
Multi-modal multi-instance learning using weakly correlated histopathological images and tabular clinical information
Hang Li, Fan Yang, Xiaohan Xing, Yu Zhao, Jun Zhang, Yueping Liu, Mengxue Han, Junzhou Huang, Liansheng Wang, Jianhua Yao.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2021).
DT-MIL: deformable transformer for multi-instance learning on histopathological image
Hang Li, Fan Yang, Yu Zhao, Xiaohan Xing, Jun Zhang, Mingxuan Gao, Junzhou Huang, Liansheng Wang, Jianhua Yao.
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2021).

Book Chapter

Deep Learning-Driven Models for Endoscopic Image Analysis
Xiao Jia, Xiaohan Xing, Yixuan Yuan, Max Q.-H. Meng.
Advances in Artificial Intelligence, Computation, and Data Science, pp 271-300.

Selected Awards

ASTRO, Best of Physics, 2024.

MICCAI Young Scientist Award, 2022.

Outstanding Graduates of Shandong Province, 2017.

Outstanding Undergraduate Thesis Award, Shandong University, 2017.

Outstanding Students Award, Shandong Province, 2016.

National Scholarship in China, 2014 & 2015 & 2016.

First-class Scholarship for Outstanding Students, Shandong University, 2014 & 2015 & 2016.

Professional Activities

Conference Service

Area Chair, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.

Session Chair, IEEE International Conference on Robotics and Automation (ICRA), 2021.

Session Chair, IEEE International Conference on Information and Automation (ICIA), 2018.
Journal Reviews

IEEE Transactions on Medical Imaging.

IEEE Journal of Biomedical and Health Informatics.

IEEE Sensors Journal.

IEEE Access.
Technical Reviewers

MICCAI, 2021 & 2022 & 2023.

ICRA, 2021.

ICIA, 2018.