Papers

2024

Peirong Liu, Oula Puonti, Annabel Sorby-Adams, William T. Kimberly, Juan E. Iglesias. “PEPSI: Pathology-Enhanced Pulse-Sequence-Invariant Representations for Brain MRI”. arXiv preprint, 2024. [code]

Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Matteen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Li, Sean I. Young, Benjamin Billot, Oula Puonti, Gordon Sze, Sam Payabvash, Adam Dehavenon, Kevin N. Sheth, Matthew S. Rosen, John Kirsch, Nicola Strisciuglio, Jelmer M. Wolterink, Arman Eshaghi, Frederik Barkhof, William T. Kimberly, Juan E. Iglesias. ”Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI.”. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024. [FreeSurfer Toolbox]

2023

Peirong Liu, Oula Puonti, Xiaoling Hu, Daniel C. Alexander, Juan E. Iglesias. “Brain-ID: Learning Robust Feature Representations for Brain Imaging”. arXiv preprint, 2023. [code]

2022

Peirong Liu, Rui Wang, Pengchuan Zhang, Omid_Poursaeed, Yipin Zhou, Xuefei Cao, Sreya Dutta Roy, Ashish Shah, Ser-Nam Lim. “Unifying Tracking and Image-Video Object Detection”. arXiv preprint, 2022.

Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer. “Deep Decomposition for Stochastic Normal-Abnormal Transport”. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, 2022. (Oral - 4%) [code]

Maxime Oquab, Daniel Haziza, Ludovic Schwartz, Tao Xu, Katayoun Zand, Rui Wang, Peirong Liu, Camille Couprie. “Efficient conditioned face animation using frontally-viewed embedding”. arXiv preprint, 2022.

2021

Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Maxime Oquab, Camille Couprie, Ser-Nam Lim. “Differential Motion Evolution for Fine-Grained Motion Deformation in Unsupervised Image Animation”. arXiv preprint, 2021.

Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel Hernán Curiale, Ruben San José Estépar, Raúl San Joé Estépar, Marc Niethammer. “Accurate Point Cloud Registration with Robust Optimal Transport”. Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), Virtual, 2021. [code]

Zhipeng Ding, Xu Han, Peirong Liu, Marc Niethammer. “Local Temperature Scaling for Probability Calibration”. IEEE/CVF International Conference on Computer Vision (ICCV), Virtual, 2021. [code]

Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer. “Perfusion Imaging: An Advection Diffusion Approach”. IEEE Transactions on Medical Imaging, 2021. [code]

Peirong Liu, Lin Tian, Yubo Zhang, Stephen R. Aylward, Yueh Z. Lee, Marc Niethammer. “Discovering Hidden Physics Behind Transport Dynamics”. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, 2021. (Oral - 3.7%) [code]

2020

Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer. “Perfusion Imaging: A Data Assimilation Approach”. arXiv preprint, 2020.

Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer. “PIANO: Perfusion Imaging via Advection-Diffusion”. Medical Image Computing and Computer Assisted Intervention (MICCAI), Virtual, 2020. (Oral, Early accept - 13%) [code]

Lin Tian, Connor Puett, Peirong Liu, Zhengyang Shen, Stephen Aylward, Yueh Lee, Marc Niethammer. “Fluid Registration Between Lung CT and Stationary Chest Tomosynthesis Images”. Medical Image Computing and Computer Assisted Intervention (MICCAI), Virtual, 2020. [code]

2019

Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, Dinggang Shen. “Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces”. Information Processing in Medical Imaging (IPMI), Hong Kong, 2019. (Oral - 10%)