Liangqiong Qu

According to our database, Liangqiong Qu authored at least 48 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning Self- and Cross-Triplet Context Clues for Human-Object Interaction Detection.

Weihong Ren, Jinguo Luo, Weibo Jiang, Liangqiong Qu, Zhi Han, Jiandong Tian, Honghai Liu

IEEE Trans. Circuits Syst. Video Technol., October, 2024

FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning.

Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan L. Yuille, Cihang Xie, Yuyin Zhou

Trans. Mach. Learn. Res., 2024

MCDNet: An Infrared Small Target Detection Network Using Multi-Criteria Decision and Adaptive Labeling Strategy.

Tianlei Ma, Qi Ma, Zhen Yang, Jing J. Liang, Jun Fu, Yu Dou, Yanan Ku, Usman Ahmad, Liangqiong Qu

IEEE Trans. Geosci. Remote. Sens., 2024

Privacy preservation for federated learning in health care.

Sarthak Pati, Sourav Kumar, Amokh Varma, Brandon Edwards, Charles Lu, Liangqiong Qu, Justin J. Wang, Anantharaman Lakshminarayanan, Shih-han Wang, Micah J. Sheller, Ken Chang, Praveer Singh, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Spyridon Bakas

Patterns, 2024

Selective Aggregation for Low-Rank Adaptation in Federated Learning.

Pengxin Guo, Shuang Zeng, Yanran Wang, Huijie Fan, Feifei Wang, Liangqiong Qu

CoRR, 2024

Tackling Data Heterogeneity in Federated Learning via Loss Decomposition.

Shuang Zeng, Pengxin Guo, Shuai Wang, Jianbo Wang, Yuyin Zhou, Liangqiong Qu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion.

Sharut Gupta, Ken Chang, Liangqiong Qu, Aakanksha Rana, Syed Rakin Ahmed, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Praveer Singh

Proceedings of the Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine, 2024

See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning.

Chengxin Zheng, Junzhong Ji, Yanzhao Shi, Xiaodan Zhang, Liangqiong Qu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Residual Denoising Diffusion Models.

Jiawei Liu, Qiang Wang, Huijie Fan, Yinong Wang, Yandong Tang, Liangqiong Qu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection.

Weibo Jiang, Weihong Ren, Jiandong Tian, Liangqiong Qu, Zhiyong Wang, Honghai Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Breast Tumor Segmentation in DCE-MRI With Tumor Sensitive Synthesis.

Shuai Wang, Kun Sun, Li Wang, Liangqiong Qu, Fuhua Yan, Qian Wang, Dinggang Shen

IEEE Trans. Neural Networks Learn. Syst., August, 2023

A Decoupled Multi-Task Network for Shadow Removal.

Jiawei Liu, Qiang Wang, Huijie Fan, Wentao Li, Liangqiong Qu, Yandong Tang

IEEE Trans. Multim., 2023

Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging.

Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou

IEEE Trans. Medical Imaging, 2023

DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Macular Hole Reconstruction with Stochastic Retinal Defect Augmentation and Dynamic Weight Composition.

Xingru Huang, Yihao Guo, Jian Huang, Zhi Li, Tianyun Zhang, Kunyan Cai, Gaopeng Huang, Wenhao Chen, Zhaoyang Xu, Liangqiong Qu, Ji Hu, Tingyu Wang, Shaowei Jiang, Chenggang Yan, Yaoqi Sun, Xin Ye, Yaqi Wang

CoRR, 2023

Granularity Matters: Pathological Graph-driven Cross-modal Alignment for Brain CT Report Generation.

Yanzhao Shi, Junzhong Ji, Xiaodan Zhang, Liangqiong Qu, Ying Liu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models.

Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled Kamal Saab, Tina Baykaner, Christopher Lee-Messer, Daniel L. Rubin

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging.

Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin

IEEE J. Biomed. Health Informatics, 2022

A cascaded nested network for 3T brain MR image segmentation guided by 7T labeling.

Jie Wei, Zhengwang Wu, Li Wang, Toan Duc Bui, Liangqiong Qu, Pew-Thian Yap, Yong Xia, Gang Li, Dinggang Shen

Pattern Recognit., 2022

Relation constraint self-attention for image captioning.

Junzhong Ji, Mingzhan Wang, Xiaodan Zhang, Minglong Lei, Liangqiong Qu

Neurocomputing, 2022

Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models.

Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled Kamal Saab, Christopher Lee-Messer, Daniel L. Rubin

CoRR, 2022

Masked Co-attentional Transformer reconstructs 100x ultra-fast/low-dose whole-body PET from longitudinal images and anatomically guided MRI.

Yan-Ran Wang, Liangqiong Qu, Natasha Diba Sheybani, Xiaolong Luo, Jiangshan Wang, Kristina Elizabeth Hawk, Ashok Joseph Theruvath, Sergios Gatidis, Xuerong Xiao, Allison Pribnow, Daniel L. Rubin, Heike E. Daldrup-Link

CoRR, 2022

Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning.

Liangqiong Qu, Yuyin Zhou, Paul Pu Liang, Yingda Xia, Feifei Wang, Ehsan Adeli, Li Fei-Fei, Daniel L. Rubin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract.

Shuai Wang, Yang Cong, Hancan Zhu, Xianyi Chen, Liangqiong Qu, Huijie Fan, Qiang Zhang, Mingxia Liu

IEEE J. Biomed. Health Informatics, 2021

Publisher Correction: Learning MRI artefact removal with unpaired data.

Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap

Nat. Mach. Intell., 2021

Learning MRI artefact removal with unpaired data.

Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap

Nat. Mach. Intell., 2021

Learning MRI Artifact Removal With Unpaired Data.

Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap

CoRR, 2021

An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging.

Liangqiong Qu, Niranjan Balachandar, Daniel L. Rubin

CoRR, 2021

Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging.

Liangqiong Qu, Niranjan Balachandar, Miao Zhang, Daniel L. Rubin

CoRR, 2021

Addressing catastrophic forgetting for medical domain expansion.

Sharut Gupta, Praveer Singh, Ken Chang, Liangqiong Qu, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer

CoRR, 2021

2020

Code used in article "Learning MRI artefact removal with unpaired data".

Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap

Dataset, April, 2020

CT Male Pelvic Organ Segmentation via Hybrid Loss Network With Incomplete Annotation.

Shuai Wang, Dong Nie, Liangqiong Qu, Yeqin Shao, Jun Lian, Qian Wang, Dinggang Shen

IEEE Trans. Medical Imaging, 2020

Iterative Label Denoising Network: Segmenting Male Pelvic Organs in CT From 3D Bounding Box Annotations.

Shuai Wang, Qian Wang, Yeqin Shao, Liangqiong Qu, Chunfeng Lian, Jun Lian, Dinggang Shen

IEEE Trans. Biomed. Eng., 2020

Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains.

Liangqiong Qu, Yongqin Zhang, Shuai Wang, Pew-Thian Yap, Dinggang Shen

Medical Image Anal., 2020

The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions.

Sharut Gupta, Praveer Singh, Ken Chang, Mehak Aggarwal, Nishanth Thumbavanam Arun, Liangqiong Qu, Katharina Hoebel, Jay B. Patel, Mishka Gidwani, Ashwin Vaswani, Daniel L. Rubin, Jayashree Kalpathy-Cramer

CoRR, 2020

Federated Learning for Breast Density Classification: A Real-World Implementation.

Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer

Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020

2019

Wavelet-based Semi-supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI.

Liangqiong Qu, Shuai Wang, Pew-Thian Yap, Dinggang Shen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018

Evaluation of shadow features.

Liangqiong Qu, Jiandong Tian, Huijie Fan, Wentao Li, Yandong Tang

IET Comput. Vis., 2018

2017

RGBD Salient Object Detection via Deep Fusion.

Liangqiong Qu, Shengfeng He, Jiawei Zhang, Jiandong Tian, Yandong Tang, Qingxiong Yang

IEEE Trans. Image Process., 2017

A New Intrinsic-Lighting Color Space for Daytime Outdoor Images.

Zhi Han, Jiandong Tian, Liangqiong Qu, Yandong Tang

IEEE Trans. Image Process., 2017

A hand pose tracking benchmark from stereo matching.

Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, Xiaobin Xu, Qingxiong Yang

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

DeshadowNet: A Multi-context Embedding Deep Network for Shadow Removal.

Liangqiong Qu, Jiandong Tian, Shengfeng He, Yandong Tang, Rynson W. H. Lau

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

New spectrum ratio properties and features for shadow detection.

Jiandong Tian, Xiaojun Qi, Liangqiong Qu, Yandong Tang

Pattern Recognit., 2016

3D Hand Pose Tracking and Estimation Using Stereo Matching.

Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, Xiaobin Xu, Qingxiong Yang

CoRR, 2016

2015

Object Color Constancy for Outdoor Multiple Light Sources.

Liangqiong Qu, Zhigang Duan, Jiandong Tian, Zhi Han, Yandong Tang

Proceedings of the Computer Vision - CCF Chinese Conference, 2015

Shadow generation on an image based on tricolor linear attenuation model.

Zhigang Duan, Jiandong Tian, Liangqiong Qu, Yandong Tang, Yang Cong

Proceedings of the 10th International Conference on Information, 2015

2014

Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and Shadow-free Image.

Liangqiong Qu, Jiandong Tian, Zhi Han, Yandong Tang

CoRR, 2014