Xuzhe Zhang 张旭哲

A lifelong learner

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I am interested in studying AI-empowered medical imaging acquisition, processing, and interpretation to transform medical research and clinical practice. My research is multidisciplinary, building on techniques in deep learning, computer vision, and medical imaging. I am interested in developing robust vision models for medical image analysis and computing. My research focused on generative models, self-/semi-supervised learning, and unsupervised domain adaptation. Recently, I am exploring in-context learning in (large) vision model.

On the application side, I focused on deploying open-source frameworks in medical / clinical research communities, with the goal of assisting large-scale and cross-modality clinical studies to discover quantitative image-based markers and thereby improve healthcare.

TL;DR: Computer Vision & AI in Medical Imaging = Intelligent Vision in Healthcare

news

Feb 27, 2024 MAPSeg has been accepted at CVPR 2024! See you in Seattle!
Nov 28, 2023 Our recent work on self-supervised learning and unsupervised domain adaptation for heterogeneous medical image segmentation is now available on arXiv: MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling. MAPSeg is the first unified UDA framework that works for centralized, federated, and test-time UDA.
May 16, 2023 I started my 2023 summer internship at GE Healthcare as an AI/ML PhD Intern. I will continue my research in advancing medical vision!
May 13, 2022 Our paper PTNet3D: A 3D High-Resolution Longitudinal Infant Brain MRI Synthesizer Based on Transformers has been accepted for publication in IEEE Transactions on Medical Imaging (IEEE-TMI). link
Mar 16, 2022 I passed my qualifying exam and am officially a Ph.D. candidate!

selected publications

  1. arXiv
    MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling
    Zhang, Xuzhe, Wu, Yuhao, Angelini, Elsa, Li, Ang,  Guo, Jia and 8 more authors
    2023
  2. Journal
    PTNet3D: A 3D High-Resolution Longitudinal Infant Brain MRI Synthesizer Based on Transformers
    Zhang, Xuzhe, He, Xinzi, Guo, Jia, Ettehadi, Nabil,  Aw, Natalie and 4 more authors
    IEEE Transactions on Medical Imaging 2022