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Selected Publications (# equal contribution, * corresponding author)
Google Scholar Profile for full publication list.
Yuetan Chu#, Gongning Luo#*, Longxi Zhou#, Shaodong Cao, Guolin Ma, Xianglin Meng, Juexiao Zhou, Changchun Yang, Dexuan Xie, Ricardo Henao, Xigang Xiao, Lianming Wu, Zhaowen Qiu, Xin Gao.
Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy
.
[paper]
[code]
Nature Communications, 2025. (Top Journal in the field; IF>10) (First explanation of the difference in vascular abundance between men and women, overturning traditional anatomical cognition)
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Gongning Luo, Mingwang Xu, Hongyu Chen, Xinjie Liang, Xing Tao, Dong Ni, Hyunsu Jeong, Chulhong Kim, Raphael Stock, Michael Baumgartner, Yannick Kirchhoff, Maximilian Rokuss, Klaus Maier-Hein, Zhikai Yang, Tianyu Fan, Nicolas Boutry, Dmitry Tereshchenko, Arthur Moine, Maximilien Charmetant, Jan Sauer, Hao Du, Xiang-Hui Bai, Vipul Pai Raikar, Ricardo Montoya-del-Angel, Robert Marti, Miguel Luna, Dongmin Lee, Abdul Qayyum, Moona Mazher, Qihui Guo, Changyan Wang, Navchetan Awasthi, Qiaochu Zhao, Wei Wang, Kuanquan Wang, Qiucheng Wang, Suyu Dong.
Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge
.
[paper]
[code]
arXiv preprint arXiv:2501.15588, 2025. [Data] (The first automated 3D breast ultrasound tumor detection, segmentation and classification benchmark)
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Gongning Luo, Kuanquan Wang, Jun Liu, Shuo Li, Xinjie Liang, Xiangyu Li, Shaowei Gan, Wei Wang, Suyu Dong, Wenyi Wang, Pengxin Yu, Enyou Liu, Hongrong Wei, Na Wang, Jia Guo, Huiqi Li, Zhao Zhang, Ziwei Zhao, Na Gao, Nan An, Ashkan Pakzad, Bojidar Rangelov, Jiaqi Dou, Song Tian, Zeyu Liu, Yi Wang, Ampatishan Sivalingam, Kumaradevan Punithakumar, Zhaowen Qiu, Xin Gao.
Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge
.
[paper]
[code]
arXiv preprint arXiv:2304.03708, 2023. [Data] (The first pulmonary artery segmentation benchmark)
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Xiangyu Li, Gongning Luo*, Kuanquan Wang, Hongyu Wang, Jun Liu, Xinjie Liang, Jie Jiang, Zhenghao Song, Chunyue Zheng, Haokai Chi, Mingwang Xu, Yingte He, Xinghua Ma, Jingwen Guo, Yifan Liu, Chuanpu Li, Zeli Chen, Md Mahfuzur Rahman Siddiquee, Andriy Myronenko, Antoine P Sanner, Anirban Mukhopadhyay, Ahmed E Othman, Xingyu Zhao, Weiping Liu, Jinhuang Zhang, Xiangyuan Ma, Qinghui Liu, Bradley J MacIntosh, Wei Liang, Moona Mazher, Abdul Qayyum, Valeriia Abramova, Xavier Lladó, Shuo Li.
The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge
.
[paper]
[code]
arXiv preprint arXiv:2304.03708, 2023. [Data] (The first intracranial hemorrhage segmentation benchmark)
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Yuetan Chu, Yilan Zhang, Zhongyi Han, Changchun Yang, Longxi Zhou, Gongning Luo*, Chao Huang, Xin Gao.
Improving Representation of High-frequency Components for Medical Foundation Models.
[paper]
[code]
IEEE Transactions on Medical Imaging, 2025. (Top Journal in the field)
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Xingyu Qiu, Dong Liang, Gongning Luo*, Xiangyu Li, Wei Wang, Kuanquan Wang, Shuo Li.
MeMGB-Diff: Memory-Efficient Multivariate Gaussian Bias Diffusion Model for 3D bias field correction.
[paper]
[code]
Medical Image Analysis, 2025. (Top Journal in the field; IF>10)
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Gongning Luo, Suyu Dong, Wei Wang, Kuanquan Wang, Shaodong Cao, Clara Tam, Henggui Zhang, Joanne Howey, Pavlo Ohorodnyk, and Shuo Li.
Commensal correlation network between segmentation and direct area estimation for bi-ventricle quantification.
[paper]
[code]
Medical Image Analysis, 2020. (Top Journal in the field; IF>10)
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Gongning Luo, Wei Wang, Clara Tam, Kuanquan Wang, Shaodong Cao, Henggui Zhang, Bo Chen, and Shuo Li.
Dynamically constructed network with error correction for accurate ventricle volume estimation.
[paper]
[code]
Medical Image Analysis, 2020. (Top Journal in the field; IF>10)
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Suyu Dong, Gongning Luo, Clara Tam, Wei Wang, Kuanquan Wang, Shaodong Cao, Bo Chen, Henggui Zhang, Shuo Li.
Deep atlas network for efficient 3D left ventricle segmentation on echocardiography.
[paper]
[code]
Medical Image Analysis, 2020. (Top Journal in the field; IF>10)
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Xiangyu Li, Xinjie Liang, Gongning Luo*, Wei Wang, Kuanquan Wang, and Shuo Li.
Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning.
[paper]
[code]
Medical Image Analysis, 2023. (Top Journal in the field; IF>10)
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Zhanshi Zhu, Xinghua Ma, Wei Wang, Suyu Dong, Kuanquan Wang, Lianming Wu, Gongning Luo*, Guohua Wang, Shuo Li.
Boosting knowledge diversity, accuracy, and stability via tri-enhanced distillation for domain continual medical image segmentation.
[paper]
[code]
Medical Image Analysis, 2024. (Top Journal in the field; IF>10)
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Xiangyu Li, Gongning Luo*, Wei Wang, Kuanquan Wang, and Shuo Li.
Curriculum label distribution learning for imbalanced medical image segmentation.
[paper]
[code]
Medical Image Analysis, 2023. (Top Journal in the field; IF>10)
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Chao Ma, Gongning Luo, and Kuanquan Wang.
Concatenated and connected random forests with multiscale patch driven active contour model for automated brain tumor segmentation of MR images.
[paper]
IEEE Transactions on Medical Imaging, 2018. (Top Journal in the field) (Citations>200)
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Gongning Luo, Suyu Dong, Kuanquan Wang, Wangmeng Zuo, Shaodong Cao, and Henggui Zhang.
Multi-views fusion CNN for left ventricular volumes estimation on cardiac MR images.
[paper]
[code]
IEEE Transactions on Biomedical Engineering, 2018. (Top Journal in the field)
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Gongning Luo, Xinghua Ma, Jinwen Guo, Mingye Zou, Wei Wang, Yang Cao, Kuanquan Wang, and Shuo Li.
Trajectory-Aware Adaptive Imaging Clue Analysis for Guidewire Artifact Removal in Intravascular Optical Coherence Tomography.
[paper]
[code]
IEEE Journal of Biomedical and Health Informatics, 2023. (Top Journal in the field)
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Xiangyu Li, Gongning Luo*, Wei Wang, Kuanquan Wang, Yue Gao, and Shuo Li.
Hematoma expansion context guided intracranial hemorrhage segmentation and uncertainty estimation.
[paper]
[code]
IEEE Journal of Biomedical and Health Informatics, 2022. (Top Journal in the field)
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Xinjie Liang, Xiangyu Li, Fanding Li, Jie Jiang, Qing Dong, Wei Wang, Kuanquan Wang, Suyu Dong, Gongning Luo*, and Shuo Li.
MedFILIP: Medical Fine-Grained Language-Image Pre-Training.
[paper]
[code]
IEEE Journal of Biomedical and Health Informatics, 2025. (Top Journal in the field)
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Gongning Luo, Suyu Dong, Kuanquan Wang, Dong Zhang, Yue Gao, Xin Chen, Henggui Zhang, and Shuo Li.
A deep reinforcement learning framework for frame-by-frame plaque tracking on intravascular optical coherence tomography image.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2019. (Top Conference in the field)
(Travel Award,Top 3%;Early Accepted)
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Yuyang Zhang, Gongning Luo*, Wei Wang, Kuanquan Wang.
Branch-aware double DQN for centerline extraction in coronary CT angiography.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2020. (Top Conference in the field)
(Early Accepted)
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Suyu Dong, Gongning Luo, Kuanquan Wang, Shaodong Cao, Ashley Mercado, Olga Shmuilovich, Henggui Zhang, and Shuo Li.
VoxelAtlasGAN: 3D left ventricle segmentation on echocardiography with atlas guided generation and voxel-to-voxel discrimination.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2018. (Top Conference in the field)
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Xinghua Ma, Gongning Luo*, Wei Wang, Kuanquan Wang.
Transformer Network for Significant Stenosis Detection in CCTA of Coronary Arteries.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2021. (Top Conference in the field)
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Dong Liang, Jun Liu, Kuanquan Wang, Gongning Luo*, Wei Wang, Shuo Li.
Position-prior Clustering-based Self-attention Module for Knee Cartilage Segmentation.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2022. (Top Conference in the field)
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Xiangyu Li, Xinjie Liang, Gongning Luo*, Wei Wang, Kuanquan Wang, Shuo Li.
Ultra: Uncertainty-aware label distribution learning for breast tumor cellularity assessment.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2022. (Top Conference in the field)
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Yuetan Chu, Longxi Zhou, Gongning Luo*, Zhaowen Qiu, and Xin Gao.
Topology-Preserving Computed Tomography Super-Resolution Based on Dual-Stream Diffusion Model.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2023. (Top Conference in the field) (Star Award,Top 3%;Early Accepted)
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Yuetan Chu, Changchun Yang, Gongning Luo*, Zhaowen Qiu, and Xin Gao.
Anatomic-Constrained Medical Image Synthesis via Physiological Density Sampling.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2024. (Top Conference in the field)
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Xinghua Ma, Mingye Zou, Xinyan Fang, Yang Liu, Gongning Luo*, Wei Wang, Kuanquan Wang, Zhaowen Qiu, Xin Gao, Shuo Li.
Spatio-Temporal Contrast Network for Data-Efficient Learning of Coronary Artery Disease in Coronary CT Angiography
.
[paper]
[code]
Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference, 2024. (Top Conference in the field) (Early Accepted)
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Jun Liu, Wenyi Wang, Nuo Shen, Wei Wang, Kuanquan Wang, Qince Li, Yongfeng Yuan, Henggui Zhang, Gongning Luo*.
Spatio-Temporal Contrast Network for Data-Efficient Learning of Coronary Artery Disease in Coronary CT Angiography
.
[paper]
[code]
ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
, 2024. (Top Conference in the field) (Oral)
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Xinghua Ma, Xinyan Fang, Mingye Zou, Gongning Luo*, Wei Wang, Kuanquan Wang, Zhaowen Qiu, Xin Gao, Shuo Li.
A Trusted Lesion-assessment Network for Interpretable Diagnosis of Coronary Artery Disease in Coronary CT Angiography
.
[paper]
[code]
AAAI Conference on Artificial Intelligence (AAAI) , 2025. (Top Conference in the field)
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Xingyu Qiu, Mengying Yang, Xinghua Ma, Fanding Li, Dong Liang, Gongning Luo*, Wei Wang, Kuanquan Wang, Shuo Li
Finding Local Diffusion Schrodinger Bridge using Kolmogorov-Arnold Network
.
[paper]
[code]
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2025. (Top Conference in the field)
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Wenjian Gu, Zhanshi Zhu, Ze Liu, Yihan Wang, Yanxiao Li, Tianyi Xu, Weiping Liu, Gongning Luo*, Kuanquan Wang, Yun Zhou.
Self-supervised neural network for Patlak-based parametric imaging in dynamic [18F]FDG total-body PET
.
[paper]
European Journal of Nuclear Medicine and Molecular Imaging, 2025. (Top Journal in the field; 2022IF>10)
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Long Xu, Qiang Yang, Weihe Dong, Xiaokun Li, Kuanquan Wang, Suyu Dong, Xianyu Zhang, Tiansong Yang, Gongning Luo*, Xingyu Liao, Xin Gao, Guohua Wang
.
Meta learning for mutant HLA class I epitope immunogenicity prediction to accelerate cancer clinical immunotherapy
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[paper]
[code]
Briefings in Bioinformatics, 2025. (Top Journal in the field)
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Weihe Dong, Qiang Yang, Jian Wang, Long Xu, Xiaokun Li, Gongning Luo*, Xin Gao
.
Multi-modality attribute learning-based method for drug–protein interaction prediction based on deep neural network
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[paper]
[code]
Briefings in Bioinformatics, 2023. (Top Journal in the field)
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Gongning Luo, Dong Sui, Kuanquan Wang, Jinseok Chae
.
Neuron anatomy structure reconstruction based on a sliding filter
.
[paper]
BMC Bioinformatics, 2023.
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Gongning Luo, Ran An, Kuanquan Wang, Suyu Dong, Henggui Zhang.
A deep learning network for right ventricle segmentation in short-axis MRI
.
[paper]
[code]
Computing in Cardiology Conference (CinC), 2016. (Flagship Conference in the Field of Computational Cardiology)
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Gongning Luo, Guanxiong Sun, Kuanquan Wang, Suyu Dong, Henggui Zhang.
A novel left ventricular volumes prediction method based on deep learning network in cardiac MRI
.
[paper]
[code]
Computing in Cardiology Conference (CinC), 2016. (Flagship Conference in the Field of Computational Cardiology)
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Gongning Luo, Suyu Dong, Kuanquan Wang, Henggui Zhang.
Cardiac left ventricular volumes prediction method based on atlas location and deep learning
.
[paper]
[code]
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2016. (Flagship Conference in the Bioinformatics)
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Gongning Luo, Kuanquan Wang, Shaodong Cao, Qince Li, Henggui Zhang.
A temporal area variation regularized deep learning network for left ventricle segmentation on CMR
.
[paper]
Computing in Cardiology Conference (CinC), 2018. (Flagship Conference in the Field of Computational Cardiology)
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Gongning Luo, Kuanquan Wang, Naren Wulan, Shaodong Cao, Qince Li, Yongfeng Yuan, Henggui Zhang.
A Novel Spatio-Temporal Self-Supervised Framework to Improve the Generalization Ability for Left Ventricle Volume Quantification Based on CMR Data
.
[paper]
Computing in Cardiology Conference (CinC), 2019. (Flagship Conference in the Field of Computational Cardiology)
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