Selected Publications

You can find my full publication list on my Google Scholar profile or my Researchgate profile.

• [CVPR 2024] FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning.
  Junyuan Zhang^#, Shuang Zeng^#, Miao Zhang, Runxi Wang, Feifei Wang, Yuyin Zhou, Paul Pu Liang, Liangqiong Qu^*.
• [CVPR 2024] Residual Denoising Diffusion Models. (Paper, Code )
  Jiawei Liu, Qiang Wang, Huijie Fan^*, Yinong Wang, Yandong Tang, Liangqiong Qu^*.
• [CVPR 2024] Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding.
  Zhiheng Cheng, Qingyue Wei, Hongru Zhu, Yan Wang, Liangqiong Qu, Wei Shao, Yuyin Zhou.
• [Radiology: AI 2023] AI Transformers for Radiation Dose Reduction in Serial Whole-Body PET Scans. (Paper)
  Yan-Ran (Joyce) Wang^#, Liangqiong Qu^#, Natasha Diba Sheybani, Xiaolong Luo, Jiangshan Wang, Kristina Elizabeth Hawk, Ashok Joseph Theruvath, Sergios Gatidis, Xuerong Xiao, Allison Pribnow, Daniel Rubin, Heike E. Daldrup-Link.
• [EMNLP 2023] Granularity Matters: Pathological Graph-driven Cross-modal Alignment for Brain CT Report Generation. (Paper) (Oral)
  Yanzhao Shi, Junzhong Ji, Xiaodan Zhang^*, Liangqiong Qu^*, and Ying Liu.
• [TMI 2023] Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging. (Paper, Code)
  Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel Rubin, Lei Xing, Yuyin Zhou.
• [CHIL 2023] Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models. (Paper, Code) (Best Paper)
  Siyi Tang, Jared Dunnmon, Liangqiong Qu, Khaled Saab, Tina Baykaner, Christopher Lee-Messer, and Daniel Rubin.
• [IEEE JBHI 2022] Splitavg: A Heterogeneity-aware Federated Deep Learning Method for Medical Imaging. (Paper, Code)
  Miao Zhang^#, Liangqiong Qu ^#*, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin *.
• [IEEE CVPR 2022] Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning. (Paper, Code)
  Liangqiong Qu^#, Yuyin Zhou^#, Paul Pu Liang^#, Yingda Xia, Feifei Wang, Ehsan Adeli, Li Fei-Fei, Daniel Rubin.
• [MeDIA 2020] Synthesized 7T MRI from 3T MRI via Deep Learning in Spatial and Wavelet Domains. (Paper, Code)
  Liangqiong Qu, Yongqin Zhang, Shuai Wang, Pew-Thian Yap, Dinggang Shen.
• [MICCAI 2019] Wavelet-based Semi-supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI. (Paper) (Oral)
  Liangqiong Qu, Shuai Wang, Pew-Thian Yap, Dinggang Shen.
• [IEEE CVPR 2017] DeshadowNet: A Multi-context Embedding Deep Network for Shadow Removal. (Paper, Code, Training dataset, Test dataset) (Spotlight)
  Liangqiong Qu, Jiandong Tian, Shengfeng He, Yandong Tang, and Rynson W.H. Lau.