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Hongwei Bran Li

Hongwei Bran Li

Postdoctoral researcher at Technical University of Munich and Univerisity of Zurich
Incoming postdoc at Harvard Medical School from spring 2023

Office: TranslaTUM, Munich, Germany; USZ, Zurich, Switzerland
E-mail: hongwei D0T li AT tum.de and hongwei D0T li AT uzh.ch
[Google Scholar] [PhD Thesis] [Source Codes]

I currently work on medical image analysis and machine learning with Bjoern Menze at the University of Zurich, Benedikt Wiestler and Daniel Rueckert at TUM. I finished my Ph.D. program in medical image analysis at TUM between 09.2017 and 11.2022, spending wonderful five years in Munich and Zurich. I obtained my master degree in Informatics at Sun Yat-sen University with an eight-month exchange at CVIP group at the University of Dundee, during which I was supervised by Wei-Shi Zheng and Jianguo Zhang.

From time to time, I look for self-motivated students to explore research ideas and document the outcome. If you are interested in working with me, please send me an email about your background and research statements.

Research Interests

  • Machine learning and medical computer vision

keywords

Representative works (out of 60+ publications)

    [8] The Liver Tumor Segmentation Benchmark (LiTS), Medical Image Analysis (2022) [pdf] (cited 500+times)

    [7] Domain-adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach, MICCAI'2022 [pdf]

    [6] Imbalance-aware Self-supervised Learning for 3D Radiomic Representations, MICCAI'2021 [pdf]

    [5] 3D Deep Learning Enables Accurate Layer Mapping of 2D Materials, ACS Nano (2021) [pdf]

    [4] Automated Claustrum Segmentation in Human Brain MRI Using Deep Learning, Human Brain Mapping (2021) [pdf]

    [3] Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection, Investigative Radiology (2020) [pdf]

    [2] DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis, MICCAI'2019 [pdf] (cited 45+times)

    [1] Fully Convolutional Network Ensembles for White Matter Hyperintensities Segmentation in MR Images, NeuroImage (2018) [pdf] (cited 170+times)