Lihao Liu

Ph.D. Candidate

Cambridge Image Analysis Group
University of Cambridge
Wilberforce Road
CB3 0WA, UK

Email: ll610 at cam dot ac dot uk

Biography  

I am a Ph.D. candidate in Cambridge Image Analysis Group (CIA) and Centre for Mathematical Imaging in Healthcare (CMIH) at University of Cambridge. I am working with Carola-Bibiane Schönlieb and Angelica I. Aviles-Rivero, and Pietro Liò. Before that, I received my M.Phil. degree from Dept. of Computer Science and Engineering (CSE), Chinese University of Hong Kong, under the supervision of Prof. Pheng-Ann Heng, and my B.Eng. degree from Dept. of Software Engineering, Chongqing University.

My research interests include Medical Image Analysis and Video Understanding. Specifically, I focus on using Machine Learning techniques to solve unsupervised medical image registration and segmentation tasks. Besides, I am also working on surgical video processing, and video content understanding tasks.

News

Publications

                                                   
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios

Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Arxiv Tech Report, 2023.

[paper]

Traffic Video Object Detection using Motion Prior

Lihao Liu, Yanqi Cheng, Dongdong Chen, Jing He, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Arxiv Tech Report, 2023.

[paper]

SCOTCH and SODA: A Transformer Video Shadow Detection Framework

Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Computer Vision and Pattern Recognition (CVPR), 2023.

[paper] [project]

Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness

Yanqi Cheng, Lihao Liu, Shujun Wang, Yueming Jin, Carola-Bibiane Schönlieb, Angelica I. Aviles-Rivero.
Trustworthy Machine Learning for Healthcare (ICLR-TML4H), 2023.

[paper] [project]

TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation

Zhongying Deng, Yanqi Chen, Lihao Liu, Shujun Wang, Rihuan Ke, Carola-Bibiane Schonlieb, and Angelica I Aviles-Rivero.
Arxiv Tech Report, 2022.

[paper] [project]

PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation

Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Major Revision at Medical Image Analysis. (MIA), 2023.

[paper]

You Only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration

Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero.
Biomedical Image Registration (WBIR), 2022.

[paper]

MammoDG: Generalisable Deep Learning for Cross-Domain Multi-Center Breast Cancer Screening

Yijun Yang, Shujun Wang, Lihao Liu, Sarah Hickman, Fiona J Gilbert, Carola-Bibiane Schönlieb, Angelica I. Aviles-Rivero.
Arxiv Tech Report, 2023.

[paper]

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Simon Graham, Quoc Dang Vu, ..., Lihao Liu, Chengyang Hong, and et. al.
Medical Image Analysis (MIA), 2023.

[paper] [code] [project]

Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting

Lihao Liu, Chengyang Hong, Angelica I Aviles-Rivero, and Carola-Bibiane Schönlieb.
Medical Image Understanding and Analysis (MIUA), 2022.

[paper] [code] [algorithm]

[Merit NVIDIA Paper Award!] [Ranking 4/373 in the CoNIC-2022!]

Learning Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation

Jing Zou, Noémie Debroux, Lihao Liu, Jing Qin, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero.
Medical Image Analysis (MIA), 2023.

[paper]

Deformable Lung CT Registration by Decomposing Large Deformation

Jing Zou, Lihao Liu, Youyi Song, Kup-Sze Choi, Jing Qin.
Biomedical Image Registration (WBIR), 2022.

[paper]

Contrastive Registration for Unsupervised Medical Image Segmentation

Lihao Liu, Angelica I Aviles-Rivero, Carola-Bibiane Schönlieb.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

[paper] [code]

Ψ-Net: Stacking Densely Convolutional LSTMs for Sub-cortical Brain Structure Segmentation

Lihao Liu, Xiaowei Hu, Lei Zhu, Chi-Wing Fu, Jing Qin, and Pheng-Ann Heng.
IEEE Transactions on Medical Imaging (TMI), 2020.

[paper] [code]

Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration

Lihao Liu, Xiaowei Hu, Lei Zhu, and Pheng-Ann Heng.
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

[paper] [code]

Multi-Task Deep Model with Margin Ranking Loss for Lung Nodule Analysis

Lihao Liu, Qi Dou, Hao Chen, Jing Qin, and Pheng-Ann Heng.
IEEE Transactions on Medical Imaging (TMI), 2019.

[paper] [code]

MTMR-Net: Multi-Task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis

Lihao Liu, Qi Dou, Hao Chen, Iyiola E. Olatunji, Jing Qin, and Pheng-Ann Heng.
Deep Learning in Medical Image Analysis (MICCAI-DLMIA), 2018.

[paper] [code]

Experience

Honors & Awards

Professional Activities