Ph.D. Candidate
Medical Image Computing Laboratory (MedICL)
Department of Computer Science
Vanderbilt University
Nashville, TN, USA
Email: han.liu at vanderbilt dot edu
I am a 5th year (2023-2024) Ph.D. student in Computer Science, Vanderbilt University, supervised by Prof. Ipek Oguz and Prof. Benoit Dawant . Previously, I received the B.S degree from Department of Biomedical Engineering and Electrical Engineering in Rensselaer Polytechnic Institute in 2016, mentored by Prof. Ge Wang. In 2017, I received the M.S degree from the Department of Biomedical Engineering in Yale University, advised by Prof. James Duncan. Before joining Vanderbilt, I worked as a research associate in the Imaging Research Lab in the Department of Radiology in University of Pittsburgh, advised by Prof. Jiantao Pu.
My research interests lie in the fields of machine learning and medical image analysis. I'm especially interested in medical image computing with heterogenous, multi-modality data, such as developing (1) generative models for image synthesis, (2) self-adaptive models for missing modality problem, and (3) universal models by leveraging partially labeled datasets.
Han Liu, Yubo Fan, Zhoubing Xu, Benoit M. Dawant, and Ipek Oguz, "Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation", MICCAI Workshop BrainLes 2023
Han Liu, Zhoubing Xu, Riqiang Gao, Hao Li, Jianing Wang, Guillaume Chabin, Ipek Oguz, and Sasa Grbic, "COSST: Multi-organ Segmentation with Partially Labeled Datasets Using Comprehensive Supervisions and Self-training", IEEE Transactions on Medical Imaging
Han Liu, Hao Li, Xing Yao, Yubo Fan, Dewei Hu, Benoit M. Dawant, Vishwesh Nath, Zhoubing Xu, and Ipek Oguz, "COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation", MICCAI 2023
Han Liu, Michelle K. Sigona, Thomas J. Manuel, Li Min Chen, Charles F. Caskey, and Benoit M. Dawant, "Evaluation of synthetically generated computed tomography for use in transcranial focused ultrasound procedures", Journal of Medical Imaging 2023
Han Liu, Yubo Fan, Ipek Oguz, and Benoit M. Dawant, "Enhancing Data Diversity for Self-training Based Unsupervised Cross-modality Vestibular Schwannoma and Cochlea Segmentation", MICCAI Workshop BrainLes 2022
Han Liu, Yubo Fan, Hao Li, Jiacheng Wang, Dewei Hu, Can Cui, Ho Hin Lee, Huahong Zhang, and Ipek Oguz, "ModDrop++: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing Modalities", MICCAI 2022
Han Liu, Yubo Fan, Can Cui, Dingjie Su, Andrew McNeil, and Benoit M. Dawant, "Unsupervised Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation via Semi-supervised Learning and Label Fusion", MICCAI Workshop BrainLes 2021
Han Liu, Michelle K. Sigona, Thomas J. Manuel, Li Min Chen, Charles F. Caskey, and Benoit M. Dawant, "Synthetic CT Skull Generation for Transcranial MR Imaging–Guided Focused Ultrasound Interventions with Conditional Adversarial Networks", SPIE Medical Imaging 2022
Han Liu, Kathryn L. Holloway, Dario J. Englot, and Benoit M. Dawant, "A Multi-rater Comparative Study of Automatic Target Localization Methods for Epilepsy Deep Brain Stimulation Procedures", SPIE Medical Imaging 2022
Han Liu, Can Cui, Dario J Englot, Benoit M. Dawant, "Uncertainty Estimation for Medical Image Localization with Noisy Labels: ANT Targeting in MRI scans for Deep Brain Stimulation", Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020
Han Liu, Lei Wang, Yandong Nan, Faguang Jin, Jiantao Pu, "SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images", Computerized Medical Imaging and Graphics, 2019
CrossMoDA 2023 challenge Championship
IBM fellowship, 2019-2023
Dean's list, Rensselaer Polytechnic Institute, 2012-2015
Journal Reviewer
Medical Image Analysis (MedIA)
IEEE Journal of Biomedical and Health Informatics (JBHI)
The Journal of Machine Learning for Biomedical Imaging (MELBA)
Computers in Biology and Medicine (CIBM)
Computerized Medical Imaging and Graphics (CMIG)
Neurocomputing
Multidimensional Systems & Signal Process (MULT)
BioMed Research International
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Conference Reviewer
International Symposium on Biomedical Imaging (ISBI) 2024
Medical Image Computing and Computer Assisted Interventions (MICCAI) 2023
Medical Imaging with Deep Learning (MIDL) 2023
Medical Imaging Meets NeurIPS 2023
Medical Image Computing and Computer Assisted Interventions (MICCAI) 2022
Knowledge Discovery and Data Mining (KDD) 2021
Guest Lecture
CS-8395 (2022 Fall): Open Source Programming for Medical Image Processing
CS-6357 (2023 Fall): Open Source Programming for Medical Image Analysis