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Shuo Li

Professor, Biomedical Engineering
Professor, Computer and Data Sciences Department
AI in medical imaging
Office: 517B Wickenden
Email: shuo.li11@case.edu

Job Description

Dr. Li is a global leader in conducting multi-disciplinary research to enable artificial intelligence (AI) in clinical imaging. He is an academic AI scientist with a background in machine learning, medical data analytics, and imaging. His current research focuses on the development of image-centered AI systems. These systems are designed to solve the most challenging clinical and fundamental data analytics problems in various fields, including cardiology, radiology, urology, surgery, rehabilitation, and cancer. He emphasizes innovations in multiple learning schemes such as deep, regression, reinforcement, adversarial, sparse, spectral, and manifold learning. Dr. Li serves as a committee member for multiple highly influential conferences and societies. He is most notable for his role on the prestigious board of directors of the MICCAI Society, a position he held from 2015 to 2024, and as the general chair of the MICCAI 2022 conference. With over 200 publications, Dr. Li has also acted as the editor for six Springer books and is an associate editor for several prestigious journals. He has received numerous awards from GE, various institutes, and international organizations throughout his career.
 

Recent Activities

  1. General Chair - MICCAI 2022 in Singapore

  2. Board of Directors (2016-2024) - MICCAI Society

 

Awards

  1. MICCAI Elsevier MedIA MICCAI 2022 Special Issue Best Paper Award, Runner Up (First author: Chenchu Xu)

  2. International Conference on Artificial Intelligence 2021 Best Student Paper (the first author: Zhiyuan Zhu) 

  3. MICCAI Young Scientist Award 2017 (First author: Wufeng Xue)

  4. Annual Award for Academic Excellence in Research, Department of Medical Imaging, Western University, 2017

  5. Above & Beyond Award, General Electric, 2014

  6. GE Innovation Award, 2009

  7. GE Management Award, 2008

  8. GE Hero Award, 2008

  9. Doctoral Prize – Distinction, Concordia University, 2007

 

Postdoc Hiring (Machine Learning and Medical Image Analysis)

We are hiring multiple postdoc fellows in AI-in-imaging. Excellent candidates with strong records in machine learning and medical image analysis are encouraged to apply. Email Dr. Shuo Li your CV and three representative publications for consideration.

Publications (Full Text Available at https://www.researchgate.net/profile/Shuo-Li-42/)

Journal articles 182 total:

  1. Zhanshi Zhu, Xinghua Ma, Wei Wang, Suyu Dong, Kuanquan Wang, Lianming Wu, Gongning Luo, Guohua Wang, and Shuo Li (2024), Boosting knowledge diversity, accuracy, and stability via tri-enhanced distillation for domain continual medical image segmentation. Medical Image Analysis, 94:103112.

  2. Xiaoming Qi, Yuting He, Guanyu Yang, Yang Chen, Jian Yang, Wangyan Liu, Yi Xu, Huazhong Shu, and Shuo Li (2024), STANet: Spatio-Temporal Adaptive Network and Clinical Prior Embedding Learning for 3D+T CMR Segmentation. IEEE Journal of Biomedical and Health Informatics(J-BHI), In Press, Online Early Access Available.

  3.  Shun Xiang, Nana Li, Yuanquan Wang, Shoujun Zhou, Jin Wei,  and Shuo Li (2024), Automatic Delineation of the 3D Left Atrium from LGE-MRI: Actor-Critic based Detection and Semi-Supervised Segmentation. IEEE Journal of Biomedical and Health Informatics(J-BHI), In Press, Online Early Access Available.

  4.  Yankun Cao, Wenzhen Zhang, Yuezhong Zhang, Guanjie Sun, Wei Guo, Mingjie Shao, Subhas Chandra Mukhopadhyay, Yujun Li, Zhi Liu, and Shuo Li (2024), CMAR: A Pipeline for Cross-Modal Alignment and 3D Reconstruction of Coronary Arteries Based on Key Bifurcation Vessel Measurements. IEEE Transactions on Instrumentation & Measurement, In Press, Online Early Access Available.

  5. Sojin Youn Wass, Omar Hahad, Zain Asad, Shuo Li, Mina K. Chung, Emelia J. Benjami, Khurram Nasi, Sanjay Rajagopalan, Sadeer G. Al-Kindi (2024), The Environmental Exposome and Atrial Fibrillation: Emerging Evidence and Future Directions. Circulation Research, 134:1029–1045.

  6. Zainab Albar, Nour Tashtish, Pedro RVO Salerno, Zhuo Chen, Shuo Li, Santosh Kumar Sirasapalli, Khurram Nasir, Khurram Nasi, Sanjay Rajagopalan, Sadeer G. Al-Kindi (2024), Coronary Artery Calcium Score, Social Vulnerability and Incident Cardiovascular Events. Journal of the American College of Cardiology, 134:1029–1045.

  7. Zhongyi Han, Xian-Jin Gui, Haoliang Sun, Yilong Yin, and Shuo Li (2023), Towards Accurate and Robust Adaptation Under Multiple Noisy Environments. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45:6460-6479.

  8. Chenchu Xu, Dong Zhang, Yuhui Song, Leonardo Kayat Bittencourt, Sree Harsha Tirumani, and Shuo Li (2023), Spatiotemporal knowledge teacher-student reinforcement learning to detect liver tumors without contrast agents. Medical Image Analysis (MedIA), 90:102980

  9. Xiangyu Li, Gongning Luo, Wei Wang, Kuanquan Wang, Shuo Li (2023), Curriculum label distribution learning for imbalanced medical image segmentation. Medical Image Analysis (MedIA), 89:102911.

  10. Shen Zhao, Jinhong Wang, Xinxin Wang, Yikang Wang, Hanying Zheng, Bin Chen, An Zeng, Fuxin Wei, Sadeer Al-Kindi, Shuo Li (2023), Attractive deep morphology-aware active contour network for vertebral body contour extraction with extensions to heterogeneous and semi-supervised scenarios. Medical Image Analysis (MedIA), 89:102906.

  11. Kaini Wang, Shuaishuai Zhuang, Juzheng Miao, Yang Chen, Jie Hua, Guang-Quan Zhou, Xiaopu He, and Shuo Li (2023), Adaptive Frequency Learning Network With Anti-Aliasing Complex Convolutions for Colon Diseases Subtypes. IEEE Journal of Biomedical and Health Informatics(J-BHI), 27:4816-4827.

  12. Gongning Luo, Xinghua Ma, Jinwen Guo, Mingye Zou, Wei Wang, Yang Cao, Kuanquan Wang, and Shuo Li (2023), Trajectory-aware Adaptive Imaging Clue Analysis for Guidewire Artifact Removal in Intravascular Optical Coherence Tomography. IEEE Journal of Biomedical and Health Informatics(J-BHI), 27:4293-4304.

  13. Xiangyu Li, Gongning Luo, Wei Wang, Kuanquan Wang, Shuo Li (2023), Ambiguity-aware Breast Tumor Cellularity Estimation Via Self-ensemble Label Distribution Learning. Medical Image Analysis (MedIA), 90:102944.

  14. Gui-Bin Bian, Wen-Qian Yue, Zhen Li, Kuanquan Wang, Shuai Zhang, Wei-Peng Liu, Shuo Li, Elias Paulino Medeiros, Wan-Qing Wu, Victor Albuquerque (2023), Variation-learning high-resolution network for capsulorhexis recognition of cataract surgery. Applied Soft Computing, 147:110841.

  15.   Shimeng Yang, Teng Li, Shuo Li (2023), Carotid Lumen Diameter and Intima-media Thickness Measurement via Boundary-guided Pseudo-labeling. IEEE Signal Processing Letters, 30:1027-1031.

  16.   Rongjun Ge, Fanqi Shi, Yang Chen, Shujun Tang, Hailong Zhang, Xiaojian Lou, Wei Zhao, Gouenou Coatrieux, Dazhi Gao, Shuo Li, and Xiaoli Mai (2023), Improving anisotropy resolution of computed tomography and annotation using 3D super-resolution network. Biomedical Signal Processing and Control, 82: 104590.

  17.   Guanyu Yang, Yuting He, Yang Lv, Yang Chen, Jean-Louis Coatrieux, Xiaoxuan Sun, Yongyue Wei, Shuo Li, and Yinsu Zhu (2023), Multi-task Learning for Pulmonary Arterial Hypertension Prognosis Prediction via Memory Drift and Prior Prompt Learning on 3D Chest CT. IEEE Journal of Biomedical and Health Informatics(J-BHI), 27: 1967-1978.

  18.   Shen Zhao, Xiangsheng Li, Jiayi He, Bin Chen, and Shuo Li (2023), Sequence based local-global information fusion framework for vertebrae detection under pathological and FOV variation challenges. Computerized Medical Imaging and Graphics (CMIG), 108: 102244.

  19.   Xifeng Hu, Yankun Cao, Weifeng Hu, Wenzhen Zhang, Jing Li, Chuanyu Wang, Subhas Chandra Mukhopadhyay, Yujun Li, Zhi Liu, and Shuo Li (2023), Refined Feature-based Multi-frame and Multi-scale Fusing Gate Network for Accurate Segmentation of Plaques in Ultrasound Videos. Computers in Biology and Medicine, 163: 107091.

  20.   Chenyi Zeng, Shen Zhao, Bin Chen, An Zeng, and Shuo Li (2023), Feature-correlation-aware History-preserving-sparse-coding Framework for Automatic Vertebrae Recognition. Computers in Biology and Medicine, 160:106977.

  21.   Yinli Tian, Wenjian Qin, Fei Xue, Ricardo Lambo, Meiyan Yue, Songhui Diao, Lequan Yu, Yaoqin Xie, Hailin Cao, and Shuo Li, ARR-GCN: Anatomy-Relation Reasoning Graph Convolutional Network for Automatic Fine-grained Segmentation of Organ’s Surgical Anatomy. IEEE Journal of Biomedical and Health Informatics(J-BHI), 27:3258-3269.

  22.   Dong Zhang, Chenchu Xu, and Shuo Li (2023), Heuristic multi-modal integration framework for liver tumor detection from multi-modal non-enhanced MRIs. Expert Systems With Applications, 221: 119782.

  23.   Xiangmin Han, Bangming Gong, Lehang Guo, Jun Wang, Shihui Ying, Shuo Li, and Jun Shi (2023), B-mode ultrasound based CAD for liver cancers via multi-view privileged information learning. Neural networks, 164: 369-381.

  24.   Ziyue Jiang, Yuting He, Shuai Ye, Pengfei Shao, Xiaomei Zhu, Yi Xu, Yang Chen, Jean-Louis Coatrieux, Shuo Li, and Guanyu Yang (2023), O2M-UDA: Unsupervised dynamic domain adaptation for one-to-multiple medical image segmentation. Knowledge-Based Systems, 265: 110378.

  25.   Zhiyuan Zhu, Taicheng Huang, Zonglei Zhen, Boyu Wang, Xia Wu, and Shuo Li (2022), From sMRI to task-fMRI: A unified geometric deep learning framework for cross-modal brain anatomo-functional mapping. Medical Image Analysis (MedIA), 83:102681.

  26.   Zhifan Gao, Saidi Guo, Chenchu Xu, Jinglin Zhang, Mingming Gong, Javier Del Ser, and Shuo Li (2022), Multi-domain Adversarial Variational Bayesian Inference for Domain Generalization. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), In Press, Online Early Access Available.

  27.   Xingxin Xu, Qikui Zhu, Jiongcheng Li, Hanning Ying, Xiujun Cai, Shuo Li, Xiaoqing Liu, and Yizhou Yu (2022), A Knowledge-guided Framework for Fine-grained Classification of Liver Lesions based on Multi-phase CT Images. IEEE Journal of Biomedical and Health Informatics(J-BHI), 27:386-396.

  28.   Chenchu Xu, Yifei Wang, Dong Zhang, Longfei Han, Yanping Zhang, Jie Chen, and Shuo Li (2022), BMAnet: Boundary Mining with Adversarial Learning for Semi-supervised 2D Myocardial Infarction Segmentation. IEEE Journal of Biomedical and Health Informatics(J-BHI), 27:87-96.

  29.   Liansheng Wang, Jiacheng Wang, Lei Zhu, Huazhu Fu, Ping Li, Gary Cheng, Zhipeng Feng, Shuo Li, and Pheng-Ann Heng (2022), Dual Multi-scale Mean Teacher Network for Semi-supervised Infection Segmentation in Chest CT Volume for COVID-19. IEEE Transactions on Cybernetics, 53:6363-6375.

  30.   Xiaojiao Xiao, Jianfeng Zhao, and Shuo Li (2022), Task Relevance Driven Adversarial Learning for Simultaneous Detection, Size Grading, and Quantification of Hepatocellular Carcinoma via Integrating Multi-modality MRI. Medical Image Analysis (MedIA), 81:102554.

  31.   Yuting He, Rongjun Ge, Xiaoming Qi, Yang Chen, Jiasong Wu, Jean-Louis Coatrieux, Guanyu Yang, and Shuo Li (2022), Learning Better Registration to Learn Better Few-Shot Medical Image Segmentation: Authenticity, Diversity, and Robustness. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), In Press, Online Early Access Available.

  32.   Chenji Zhao, Shun Xiang, Yuanquan Wang, Zhaoxi Cai, Jun Shen, Shoujun Zhou, Di Zhao, Weihua Su, Shijie Guo, and Shuo Li (2022), Context-aware Network Fusing Transformer and V-Net for Semi-supervised Segmentation of 3D Left Atrium. Expert Systems With Applications, 214:119105.

  33.   Tao Tan, Ravi Soni, Jungong Han, and Shuo Li (2022), Guest Editorial Artificial Intelligence in Pre-DICOM. IEEE Journal of Biomedical and Health Informatics(J-BHI), 9:4357-4358.

  34.   Kuanquan Wang, Shuo Li, Xiuying Wang, Jun Feng and Yong Xu (2022), Editorial: Intelligent analysis of biomedical imaging data for precision medicine. Frontiers in Medicine, 9:1017751.

  35.   Ranran Zhang, Yankun Cao, Yujun Li, Zhi Liu, Jianye Wang, Jiahuan He, Chaoyang Zhang, Xiaoyv Sui, Pengfei Zhang, Lizhen Cui, and Shuo Li (2022), MVFStain: Multiple virtual functional stain histopathology images generation based on specific domain mapping. Medical Image Analysis (MedIA), 80:102520.

  36.   Yashu Liu, Wei Wang, Gongling Luo, Dong Liang, Kuanquan Wang, and Shuo Li (2022), Uncertainty-Guided Symmetric Multi-Level Supervision Network for 3D Left Atrium Segmentation in Late Gadolinium-Enhanced MRI. Medical Physics, 49:4554-4565.

  37.   Rongjun Ge, Cong Xia, Yuting He, Hailong Sun, Daoqiang Zhang, Guanyu Yang, Wentao Xiang, Jinjun Shi, Limin Luo, Yinsu Zhu, Shuo Li and Yang Chen (2022), RE-3DLVNet: Refined estimation of the left ventricle volume via interactive 3D segmentation and reinforced quantification. Knowledge-Based Systems, 25:109212.

  38.   Yashu Liu, Wei Wang, Gongning Luo, Kuanquan Wang, and MVFStain (2022), A Contrastive Consistency Semi-supervised Left Atrium Segmentation Model. Computerized Medical Imaging and Graphics (CMIG), 99:102092.

  39.   Shen Zhao, Bin Chen, Heyou Chang, Bo Chen, and Shuo Li (2022), Reasoning discriminative dictionary-embedded network for fully automatic vertebrae tumor diagnosis. Medical Image Analysis (MedIA), 79:102456.

  40.   Yashu Liu, Wei Wang, Gongling Luo, Dong Liang, Shuo Li, and Kuanquan Wang (2022), Uncertainty-Guided Symmetric Multi-Level Supervision Network for 3D Left Atrium Segmentation in Late Gadolinium-Enhanced MRI. Medical Physics, 49:4554-4565.

  41.   Wufeng Xue, Zejian Chen, Tianfu Wang, Shuo Li, and Dong Ni (2022), Regional Cardiac Motion Scoring with Multi-scale Motion-based Spatial Attention. IEEE Journal of Biomedical and Health Informatics(J-BHI), 26: 3116-3126.

  42.   Xiaoxiao Cui, Pengfei Zhang, Yujun Li, Zhi Liu, Xiaoyan Xiao, Yang Zhang, Longkun Sun, Lizhen Cui, Guang Yang, Shuo Li (2022), MCAL: An Anatomical Knowledge Learning Model for Myocardial Segmentation in 2D Echocardiography. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 69: 1277-1287.

  43.   Huazhu Fu, Tao Zhou, Bo Chen, Shuo Li, Alejandro Frangi (2022), Guest Editorial Generative Adversarial Networks in Biomedical Image Computing. IEEE Journal of Biomedical and Health Informatics(J-BHI), 26: 4-6.

  44.   Hao Gong, Jianhua Liu, Bo Chen, Shuo Li (2022), ResAttenGAN: simultaneous segmentation of multiple spinal structures on axial lumbar MRI image using residual attention and adversarial learning. Artificial Intelligence in Medicine, 124: 102243.

  45.   Zhenyu Fang, Huimin Zhao, Jinchang Ren, Calum MacLellan, Yong Xia, and Shuo Li (2022), SC2Net: A Novel Segmentation-based Classification Network for Detection of COVID-19 in Chest X-ray Images. IEEE Journal of Biomedical and Health Informatics(J-BHI), 26: 4032-4043.

  46.   Ziqiao Wang, Zhi Liu, Shuo Li (2022), Weak Lesion Feature Extraction by Dual-branch Separation and Enhancement Network for Safe Hemorrhagic Transformation Prediction. Computerized Medical Imaging and Graphics (CMIG), 97: 102038

  47.   Ning Xiao, Wanting Yang, Qiang Yan, Juanjuan Zhao, Rui Hao, Jianhong Lian, and Shuo Li (2022), PET and CT Image Fusion of Lung Cancer with Siamese Pyramid Fusion Network. Frontiers in Medicine, 9: 792390.

  48.   Rongchang Zhao, Xuanlin Chen, Zailiang Chen, and Shuo Li (2021), Diagnosing glaucoma on imbalanced data with self-ensemble dual-curriculum learning. Medical Image Analysis (MedIA), 75:102295.

  49.   Xiaoming Qi, Yuting He, Guanyu Yang, Yang Chen, Jian Yang, Wangyan Liu, Yinsu Zhu, Yi Xu, Huazhong Shu, and Shuo Li (2021), MVSGAN: Spatial-aware Multi-view CMR Fusion for accurate 3D Left Ventricular Myocardium Segmentation. IEEE Journal of Biomedical and Health Informatics(J-BHI), 26:2264-2275

  50.   Rongjun Ge, Yuting He, Cong Xia, Chenchu Xu, Weiya Sun, Guanyu Yang, Junru Li, Zhihua Wang, Huazhong Shu, Hailing Yu, Daoqiang Zhang, Yang Chen, Limin Luo, and Shuo Li, Yinsu Zhu (2022), X-CTRSNet: 3D cervical vertebra CT reconstruction and segmentation directly from 2D X-ray images. Knowledge-Based Systems, 236:107680.

  51.   Jianfeng Zhao, Dengwang Li, Xiaojiao Xiao, Fabio Accorsi, Harry Marshall, Tyler Cossetto, Dongkeun Kim, Daniel McCarthy, Cameron Dawson, Stefan Knezevic, Bo Chen, and Shuo Li (2021), United Adversarial Learning for Liver Tumor Segmentation and Detection of Multi-modality Non-contrast MRI. Medical Image Analysis (MedIA), 73:102154.

  52.   Liansheng Wang, Cong Xie, Yi Lin, Hong-Yu Zhou, Kailin Chen, Dalong Cheng, Florian Dubost, Benjamin Collery, Bidur Khanal, Bishesh Khanal, Rong Tao, Shangliang Xu, Upasana Upadhyay Bharadwaj, Zhusi Zhong, Jie Li, Shuxin Wang, and Shuo Li (2021), Evaluation and Comparison of Accurate Automated Spinal Curvature Estimation Algorithms with Spinal Anterior-posterior X-Ray Images: The AASCE2019 Challenge. Medical Image Analysis (MedIA), 72: 102115.

  53.   Guang Yang, Heye Zhang, David Firmin, and Shuo Li (2021), Recent Advances in Artificial Intelligence for Cardiac Imaging. Computerized Medical Imaging and Graphics, 90:101928.

  54.   Tianling Lyu, Guanyu Yang, Xingran Zhao, Yang Chen, Huazhong Shu, Limin Luo, Duanduan Chen, Jiang Xiong, Jian Yang, textbfShuo Li, and Jean-Louis Coatrieux (2021), Dissected Aorta Segmentation using Convolutional Neural Networks. Computer Methods and Programs in Biomedicine, 211:106417.

  55.   Xiuquan Du, Xiaofei Xu, Heng Liu, and Shuo Li (2021), TSU-net: Two-stage multi-scale cascade and multi-field fusion U-net for right ventricular segmentation. Computerized Medical Imaging and Graphics, 93:101971.

  56.   Hao Gong, Jianhua Liu, Shuo Li, and Bo Chen (2021), Axial-SpineGAN: simultaneous segmentation and diagnosis of multiple spinal structures on axial magnetic resonance imaging images. Physics in Medicine & Biology, 66:115014.

  57.   Yuting He, Guanyu Yang, Jian Yang, Rongjun Ge, Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Huazhong Shu, Jean-Louis Dillenseger, Jean-Louis Coatrieux, and Shuo Li (2021), Meta Grayscale Adaptive Network for 3D Integrated Renal Structures Segmentation. Medical Image Analysis (MedIA), 71:102055.

  58.   Xiangyu Li, Gongning Luo, Wei Wang, Kuanquan Wang, Yue Gao, and Shuo Li (2021), Hematoma Expansion Context Guided Intracranial Hemorrhage Segmentation and Uncertainty Estimation. IEEE Journal of Biomedical and Health Informatics(J-BHI), 26: 21140-1151.

  59.   Yuting He, Tiantian Li, Rongjun Ge, Jian Yang, Youyong Kong, Huazhong Shu, Guanyu Yang, and Shuo Li (2021), Few-shot Learning for Deformable Medical Image Registration with Perception-Correspondence Decoupling and Reverse Teaching. IEEE Journal of Biomedical and Health Informatics(J-BHI), 26: 1177 - 1187.

  60.   Liyan Lin, Xi Tao, Wei Yang, Shumao Pang, Zhihai Su, Hai Lu, Shuo Li, Qianjin Feng, and Bo Chen (2021), Quantifying Axial Spine Images Using Object-specific Bi-path Network. IEEE Journal of Biomedical and Health Informatics(J-BHI), 25:2978-2987.

  61.   Chenchu Xu, Zhifan Gao, Dong Zhang, Jinglin Zhang, Lei Xu, and Shuo Li (2021), Applying Cross-modality Data Processing for Infarction Learning in Medical Internet of Things. IEEE Internet of Things Journal, 8: 16902 - 16910.

  62.   Shen Lian, Zhiming Luo, Cheng Feng, Shaozi Li, and Shuo Li (2021), APRIL: Anatomical Prior-guided ReInforcement Learning for Accurate Carotid Lumen Diameter and Intima-media Thickness Measurement. Medical Image Analysis(MedIA), 71:102040.

  63.   Chenchu Xu, Zhifan Gao, Heye Zhang, Shuo Li, and Victor Hugo C. de Albuquerque (2021), Video salient object detection using dual-stream spatiotemporal attention. Applied Soft Computing Journal, 108:107433.

  64.   Lianyi Wang, Weilan Wang, Wenjin Hu, Aaron Fenster, and Shuo Li (2021), Thanka Mural Inpainting Based on Multi-scale Adaptive Partial Convolution and Stroke-like Mask. IEEE Transactions on Image Processing (TIP), 30:3720-3733.

  65.   Wufeng Xue, Jiahui Li, Zhiqiang Hu, Eric Kerfoot, James Clough, Ilkay Oksuz, Hao Xu, Vicente Grau, Fumin Guo, Matthew Ng, Xiang Li, Quanzheng Li, Lihong Liu, Jin Ma, Elias Grinias, Georgios Tziritas, Wenjun Yan, Angélica Atehortúa, Mireille Garreau, Yeonggul Jang, Alejandro Debus, Enzo Ferrante, Guanyu Yang, Tiancong Hua, and Shuo Li (2021), Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-ventricular Short-axis Cardiac MR Data. IEEE Journal of Biomedical and Health Informatics (J-BHI), 25: 3541-3553.

  66.   Chenchu Xu, Dong Zhang, Jaron Chong, Bo Chen, and Shuo Li (2021), Synthesis of Gadolinium-enhanced Liver Tumors on Nonenhanced Liver MR Images Using Pixel-level Graph Reinforcement Learning. Medical Image Analysis(MedIA), 69:101976.

  67.   Chengqian Zhao, Dengwang Li, Cheng Feng, and Shuo Li (2021), OF-UMRN: Uncertainty-guided Multitask Regression Network Aided by Optical Flow for Fully Automated Comprehensive Analysis of Carotid Artery. Medical Image Analysis(MedIA), 70:101982.

  68.   Dong Zhang, Chenchu Xu, Jaron Chong, Bo Chen, and Shuo Li (2021), Weakly-Supervised Teacher-Student Network for Liver Tumor Segmentation from Non-enhanced Images. Medical Image Analysis(MedIA), 70:102005.

  69.   Chenchu Xu, Zhifan Gao, Dong Zhang, Jinglin Zhang, Lei Xu, and Shuo Li (2021), Applying Cross-Modality Data Processing for Infarction Learning in Medical Internet of Things. IEEE Internet of Things Journal, 8: 16902 - 16910.

  70.   Tianling Lyu, Wei Zhao, Yinsu Zhu, Zhan Wu, Yikun Zhang, Yang Chen, Limin Luo, Shuo Li, and Lei Xing (2021), Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network. Medical Image Analysis(MedIA), 70:102001.

  71.   Xiuquan Du, Jiajia Hu, and Shuo Li (2021), Use Chou’s 5-steps rule to predict DNA-protein binding with multi-scale complementary feature. Journal of Proteome Research, 20:1639-1656.

  72.   Zhi Liu, Yunhua Lu, Xiaochuan Zhang, Sen Wang, Shuo Li, and Bo Chen (2021), Multi-Indices Quantification for Left Ventricle via DenseNet and GRU-Based Encoder-Decoder with Attention. Complexity, 2021:3260259.

  73.   Shen Zhao, Xi Wu, Bo Chen, and Shuo Li (2020), Automatic Vertebrae Recognition from Arbitrary Spine MRI images by a Category Consistent Self-calibration Detection Framework. Medical Image Analysis(MedIA), 67:101826.

  74.   Dong Zhang, Bo Chen, and Shuo Li (2020), Sequential Conditional Reinforcement Learning for Simultaneous Vertebral Body Detection and Segmentation with Modeling the Spine Anatomy. Medical Image Analysis(MedIA), 67:101861.

  75.   Zhan Wu, Rongjun Ge, Minli Wen, Gaoshuang Liu, Yang Chen, Pinzheng Zhang, Xiaopu He, Hua Jie, Limin Luo, and Shuo Li (2020), Automatic Classification and Segmentation for Esophageal Lesions using Convolutional Neural Network. Medical Image Analysis(MedIA), 67:101838.

  76.   Zhongyi Han, Benzheng Wei, Bo Chen, Yilong Yin, and Shuo Li (2020), Unifying Neural Learning and Symbolic Reasoning for Spinal Medical Report Generation. Medical Image Analysis(MedIA), 67:101872.

  77.   Clara Tam, Dong Zhang, Terry Peters, Bo Chen, and Shuo Li (2020), Holistic Multitask Regression Network for Multiapplication Shape Regression Segmentation. Medical Image Analysis(MedIA), 65:101783.

  78.   Gongning Luo, Wei Wang, Clara Tam, Kuanquan Wang, Shaodong Cao, Henggui Zhang, Bo Chen, and Shuo Li (2020), Dynamically Constructed Network with Error Correction for Accurate Ventricle Volume Estimation. Medical Image Analysis(MedIA), 64:101723.

  79.   Yanan Ruan, Dengwang Li, Harry Marshall, Timothy Miao, Tyler Cossetto, Ian Chan, Omar Daher, Fabio Accorsi, Aashish Goela, and Shuo Li (2020), MB-FSGAN: Joint Segmentation and Quantification of Kidney Tumor on CT by the Multi-branch Feature Sharing Generative Adversarial Network. Medical Image Analysis(MedIA), 64:101721.

  80.   Dong Zhang, Guang Yang, Shu Zhao, Yangping Zhang, Heye Zhang, Dhanjoo Ghista, and Shuo Li (2020), Direct Quantification of Coronary Artery Stenosis through Hierarchical Attentive Multi-view Learning. IEEE Transaction on Medical Imaging (TMI), 39: 4322 - 4334.

  81.   Zhi Liu, Yihao Zhang, Weiwei Li, Shuo Li, and Zhiling Zou, and Bo Chen (2020), Multislice Left Ventricular Ejection Fraction Prediction From Cardiac MRIs without Segmentation Using Shared SptDenNet. Computerized Medical Imaging and Graphics (CMIG), 86:101795.

  82.   Chengjin Yu, Zhifan Gao, Weiwei Zhang, Guang Yang, Shu Zhao, Heye Zhang, Yanping Zhang, and Shuo Li (2020), Multi-Task Learning for Estimating Multi-Type Cardiac Indices in MRI and CT Based on Adversarial Reverse Mapping. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 32: 493-506.

  83.   Yuting He, Guanyu Yang, Jian Yang, Yang Chen, Youyong Kong, Jiasong Wu, Lijun Tang, Xiaomei Zhu, Jean-Louis Dillenseger, Pengfei Shao, Shaobo Zhang, Huazhong Shu, Jean-Louis Coatrieux, and Shuo Li (2020), Dense Biased Networks with Deep Priori Anatomy and Hard Region Adaptation: Semi-supervised Learning for Fine Renal Artery Segmentation. Medical Image Analysis (MedIA), 63:101722.

  84.   Mingchao Li, Yerui Chen, Zexuan Ji, Keren Xie, Songtao Yuan, Qiang Chen, and Shuo Li (2020), 3D to 2D Image Segmentation in OCTA Images. IEEE Transaction on Medical Imaging (TMI), 39:3343-3354.

  85.   Jianfeng Zhao, Dengwang Li, Zahra Kassam, Jaron Chong, Bo Chen, and Shuo Li (2020), Tripartite-GAN: Synthesizing Liver Contrast-Enhanced MRI to Improve Tumor Detection. Medical Image Analysis (MedIA), 63:101667.

  86.   Xiuquan Du, Yuhui Song, Yueguo Liu, Yanping Zhang, Heng Liu, Bo Chen, and Shuo Li (2020), An Integrated Deep Learning Framework for Joint Segmentation of Blood Pool and Myocardium. Medical Image Analysis (MedIA), 62:101685.

  87.   Chenchu Xu, Lei Xu, Pavlo Ohorodnyk, Mike Roth, Bo Chen, and Shuo Li (2020), Contrast Agent-free Synthesis and Segmentation of Ischemic Heart Disease Images using Progressive Sequential Causal GANs. Medical Image Analysis (MedIA), 62:101668.

  88.   Hejun Wu, Rong Gao, Yeong Poh Sheng, Bo Chen, and Shuo Li (2020), SDAE-GAN: Enable High-dimensional Pathological Images in Liver Cancer Survival Prediction with a Policy Gradient Based Data Augmentation Method. Medical Image Analysis (MedIA), 62:101640.

  89.   Beiji Zou, Zhiyou He, Rongchang Zhao, Chengzhang Zhu, Wangmin Liao, and Shuo Li, (2020), Non-rigid Retinal Image Registration using an Unsupervised Structure-driven Regression Network. Neurocomputing, 404:14-25.

  90.   Yang Chen, Wu Zhan, Layne Shi, Fei Shi, Xinjian Chen, Shuo Li, Gouenou Coatrieux, Jian Yang, and Limin Luo, (2020), Coarse-to-fine Classification for Diabetic Retinopathy Grading Using Convolutional Neural Network. Artificial Intelligence in Medicine, 108:101936.

  91.   Kumaradevan Punithakumar, Ismail Ben Ayed, Abraam S. Soliman, Aashish Goela, Ali Islam, Shuo Li, and Michelle Noga (2020), 3D Motion Estimation of Left Ventricular Dynamics Using MRI and Track-to-Track Fusion. IEEE Journal of Translational Engineering in Health and Medicine (JTEHM),8:1800209.

  92.   Guang Yang, Jun Chen, Zhifan Gao, Shuo Li, Hao Ni, Elsa Angelini, Tom Wong, Raad Mohiaddin, Eva Nyktari, Ricardo Wage, Lei Xu, Yanping Zhang, Xiuquan Du, Heye Zhang, David Firmin, and Jennifer Keegan (2020), Simultaneous Left Atrium Anatomy and Scar Segmentations via Deep Learning in Multiview Information with Attention. Future Generation Computer Systems, 107:215-228.

  93.   Yang Chen, Guanyu Yang, Tianling Lv, Yun-Peng Shen, Shuo Li, Huazhong Shu, Limin Luo, and Jean-Louis Coatrieux (2020), Vessel Structure Extraction using Constrained Minimal Path Propagation. Artificial Intelligence in Medicine, 105:101846.

  94.   Yanfei Hong, Benzheng Wei, Zhongyi Han, Xiang Li, Yuanjie Zheng, and Shuo Li (2020), MMCL-Net: Spinal Disease Diagnosis in Global Mode using Progressive Multi-task Joint Learning. Neurocomputing, 399:307-316.

  95.   Xiuquan Du, Susu Yin, Renjun Tang, Yueguo Liu, Yuhui Song, Yanping Zhang, Heng Liu, and Shuo Li (2020), Segmentation and Visualization of Left Atrium through a Unified Deep Learning Framework. International Journal of Computer Assisted Radiology and Surgery (IJCARS), 15(4):589-600.

  96.   Zhiyuan Zhu, Zonglei Zhen, Xia Wu, and Shuo Li (2020), Estimating Functional Connectivity by Integration of Inherent Brain Function Activity Pattern Priors. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18: 2420-2430.

  97.   Suyu Dong, Gongning Luo, Clara Tam, Wei Wang, Kuanquan Wang, Shaodong Cao, Bo Chen, Henggui Zhang, and Shuo Li (2020), Deep Atlas Network for Efficient 3D Left Ventricle Segmentation on Echocardiography. Medical Image Analysis (MedIA), 61:101638.

  98.   Zhifan Gao, Heye Zhang, Shizhou Dong, Shanhui Sun, Xin Wang, Guang Yang, Wanqing Wu, and Shuo Li, Victor Hugo C. de Albuquerque (2020), Salient Object Detection in the Distributed Cloud-Edge Intelligent Network. IEEE Network, 34:216-224.

  99.   Zhifan Gao, Chenchu Xu, Heye Zhang, Shuo Li, and Victor Hugo C. de Albuquerque (2020), Trustful Internet of Surveillance Things Based on Deeply-Represented Visual Co-Saliency Detection. IEEE Internet of Things Journal, 7:4092-4100.

  100.   Liyan Lin, Xi Tao, Shumao Pang, Zhihai Su, Hai Lu, Shuo Li, Qianjin Feng, and Bo Chen (2020), Multiple Axial Spine Indices Estimation via Dense Enhancing Network with Cross-space Distance-preserving Regularization. IEEE Journal of Biomedical and Health Informatics(J-BHI), 24:3248-3257.

  101.   Ranran Zhang, Xiaoyan Xiao, Zhi Liu, Yujun Li, and Shuo Li (2020), Multi-task Relational Learning Network for MRI Vertebral Localization, Identification and Segmentation. IEEE Journal of Biomedical and Health Informatics(J-BHI), 24:2902-2911.

  102.   textitRongjun Ge, Guanyu Yang, Yang Chen, Limin Luo, Cheng Feng, and Shuo Li (2020), K-Net: Integrate Left Ventricle Segmentation and Direct Quantification of Paired Echo Sequence. IEEE Transaction on Medical Imaging (TMI), 39(5):1690-1702.

  103.   Zhifan Gao, Jonathan Chung, Mohamed Abdelrazek, Stephanie Leung, William Kongto Hau, Zhanchao Xian, Heye Zhang, and Shuo Li (2019), Privileged Modality Distillation for Vessel Border Detection in Intracoronary Imaging. IEEE Transaction on Medical Imaging (TMI), 39(5):1524-1534.

  104.   Gongning Luo, Gongning Luo, Wei Wang, Kuanquan Wang, Shaodong Cao, Clara Tam, Henggui Zhang, Joanne Howey, Pavlo Ohorodnykd, and Shuo Li (2019), Commensal Correlation Network Between Segmentation and Direct Area Estimation for Bi-ventricle Qualification. Medical Image Analysis (MedIA), 59:101591.

  105.     Chenchu Xu, Joanne Howey, Pavlo Ohorodnyk, Mike Roth, Heye Zhang, and Shuo Li (2020), Segmentation and Quantification of Infarction without Contrast Agents via Spatiotemporal Generative Adversarial Learning. Medical Image Analysis (MedIA), 59:101568.

  106.     Rongjun Ge, Guanyu Yang, Yang Chen, Limin Luo, Bo Chen, Cheng Feng, Heye Zhang, and Shuo Li (2019), PV-LVNet: Direct Left Ventricle Multitype Indices Estimation from 2D Echocardiograms of Paired Apical Views with Deep Neural Networks. Medical Image Analysis (MedIA), 58:101554.

  107.     Rongchang Zhao, and Shuo Li (2020), Multi-indices Quantification of Optic Nerve Head in fundus image via Multitask Collaborative Learning. Medical Image Analysis, 58:101593.

  108.     Liansheng Wang, Qiuhao Xu, Stephanie Leung, Jonathan Chung, Bo Chen, and Shuo Li (2019), Accurate Automated Cobb Angles Estimation using Multi-View Extrapolation Net. Medical Image Analysis (MedIA), 58:101542.

  109.     Zhongyi Han, Hongbo Wu, Benzheng Wei, Yilong Yin, and Shuo Li (2020), Recursive Narrative Alignment for Movie Narrating. Science China Information Sciences, 63:1–3.

  110.     Rongchang Zhao, Xuanlin Chen, Xiyao Liu, Zailiang Chen, Fan Guo, and Shuo Li (2019), Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning. IEEE Journal of Biomedical and Health Informatics(J-BHI), 24(4):1104-1113.

  111.     Shen Zhao, Xi Wu, Bo Chen, and Shuo Li (2019), Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network. Medical Image Analysis (MedIA), 58:101533.

  112.     Zhifan Gao, Sitong Wu, Zhi Liu, Jianwen Luo, Heye Zhang, and Shuo Li (2019), Learning the Implicit Strain Reconstruction in Ultrasound Elastography Using Privileged Information. Medical Image Analysis (MedIA), 58:101513.

  113.     Xiuquan Du, Yanyu Diao, Heng Liu, and Shuo Li (2019), MsDBP: Exploring DNA-binding Proteins by Integrating Multi-scale Sequence Information via Chou’s 5-steps Rule. Journal of Proteome Research, 18:3119-3132.

  114.     Shumao Pang, Zhihai Su, Stephanie Leung, Ilanit Ben Nachum, Bo Chen, Qianjing Feng, and Shuo Li (2019), Direct Automated Quantitative Measurement of Spine by Cascade Amplifier Regression Network with Manifold Regularization. Medical Image Analysis (MedIA), 55:103-115.

  115.     Wenji Wang, Yuanquan Wang, Yuwei Wu, Tao Lin, Shuo Li, and Bo Chen (2019), Quantification of Full Left Ventricular metrics via Deep Regression Learning with Contour-guidance, IEEE Access, 7:47918 - 47928

  116.     Longwei Fang, Zuowei Wang, Zhiqiang Chen, Fengzeng Jian, Shuo Li, and Huiguang He (2019), 3D Shape Reconstruction of Lumbar Vertebra from Two X-ray Images and a CT Model. IEEE/CAA Journal of Automatica Sinica, 7:1124-1133.

  117.     Qing Liu, Xiaopeng Hong, Shuo Li, Zailiang Chen, Guoying Zhao, and Beiji Zou (2019), A Spatial-aware Joint Optic Disc and Cup Segmentation Method. Neurocomputing, 359:285-297.

  118.     Xiuquan Du, Renjun Tang, Susu Yin, Yanping Zhang, and Shuo Li (2019), Direct Segmentation-based Full Quantification for Left Ventricle via Deep Multi-task Regression Learning Network. IEEE Journal of Biomedical and Health Informatics(J-BHI), 23:942-948.

  119.     Chenchu Xu, Lin Xu, Yanping Zhang, Heye Zhang, Xiuquan Du, and Shuo Li (2019), A Novel Machine-learning Algorithm to Estimate the Position and Size of Myocardial Infarction for CMR Sequence. Computing, 101:653–665.

  120.     Weiwei Zhang, Xiuquan Du, Jinglin Zhang, Yanping Zhang, and Shuo Li (2019), An End-to-End Joint Learning Framework of Artery-specic Coronary Calcium Scoring in Non-contrast Cardiac CT Computing. Computing, 101:667-678.

  121.     Jingyu Cong, Yuanjie Zheng, Wufeng Xue, Bofeng Cao, and Shuo Li (2019), MA-Shape: Modality Adaptation Shape Regression for Left Ventricle Segmentation on Mixed MR and CT Images. IEEE Access, 7:16584-16593.

  122.     Zhongyi Han, Benzheng Wei, Ashley Mercado, Stephanie Leung, and Shuo Li (2018), Spine-GAN: Semantic Segmentation of Multiple Spinal Structures. Medical Image Analysis (MedIA), 50:23-35.

  123.     Chenchu Xu, Lei Xu, Zhifan Gao, Shen Zhao, Heye Zhang, Yanping Zhang, Xiuquan Du, Shu Zhao, Dhanjoo Ghista, Huafeng Liu, and Shuo Li (2018), Direct Delineation of Myocardial Infarction without Contrast Agents using a Joint Motion Feature Learning Architecture. Medical Image Analysis (MedIA), 50:82-94.

  124.     Hongbo Wu, Chris Bailey, Parham Rasoulinejad, and Shuo Li (2018), Automated Comprehensive Adolescent Idiopathic Scoliosis Assessment using MVC-Net. Medical Image Analysis (MedIA), 48:1-11.

  125.     Wenbo Sun, Zhao Ruan, Xuan Dai, Sirui Li, Shuo Li, Jianjian Zhang, Jincao Chen, Heye Zhang, Heye Zhang, and Haibo Xu (2018), Quantifying Hemodynamics Changes in Moyamoya Disease based on 2D Cine Phase-Contrast MRI and Computational Fluid Dynamics. World Neurosurgery, 120: 1301-1309.

  126.     Xiantong Zhen, Mengyang Yu, Xiaofei He, and Shuo Li (2018), Multi-Target Regression via Robust Low-Rank Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 40:497-504.

  127.     Zhongyi Han, Benzheng Wei, Stephanie Leung, Ilanit Ben Nachum, David Laidley, and Shuo Li (2018), Automated Pathogenesis-based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning. Neuroinformatics, 16:325-337.

  128.     Jun Chen, Heye Zhang, Weiwei Zhang, Xiuquan Du, Yanping Zhang, and Shuo Li (2018), Correlated Regression Feature Learning for Automated Right Ventricle Segmentation. IEEE Journal of Translational Engineering in Health and Medicine (JTEHM), 6:1-10.

  129.     Bin Gu, Yingying Shan, Victor S. Sheng, and Shuo Li (2018), Sparse Regression with Output Correlation for Cardiac Ejection Fraction Estimation. Information Sciences, 423: 303-312.

  130.     Xiaoxu He, Stephanie Leung, James Warrington, Olga Shmuilovich, and Shuo Li (2018), Automated Neural Foraminal Stenosis Grading via Task-aware Structural Representation Learning. Neurocomputing, 287: 185-195.

  131.     Shen Zhao, Zhifan Gao, Heye Zhang, Yaoqin Xie, Dhanjoo Ghista, Zhongong Wei, Xiaojun Bi, Huahua Xiong, Chenchu Xu, and Shuo Li (2018), Robust Segmentation of Intima-Media Borders with Different Morphologies and Dynamics During the Cardiac Cycle. IEEE Journal of Biomedical and Health Informatics (J-BHI), 22: 1571-1582.

  132.     Xiuquan Du, Yu Yao, Yanyu Diao, Huaixu Zhu, Yanping Zhang, and Shuo Li (2018), DeepSS: Exploring Splice Site Motif through Convolutional Neural Network Directly from DNA sequence. IEEE Access, 6:32958-32978.

  133.     Xiuquan Du, Weiwei Zhang, Heye Zhang, Jun Chen, Yanping Zhang, James Claude Warrington, Gary Brahm, and Shuo Li (2018), Deep Regression Segmentation for Cardiac Bi-ventricle MR Images. IEEE Access, 6:3828-3838.

  134.     Yufa Xia, Huailing Zhang, Lin Xu, Zhifan Gao, Heye Zhang, Huafeng Liu, and Shuo Li (2018), An Automatic Cardiac Arrhythmia Classification System with Wearable Electrocardiogram. IEEE Access, 6:16529-16538.

  135.     Qingneng Li, Zhifan Gao, Qinyu Wang, Jun Xia, Heye Zhang, Huailing Zhang, Huafeng Liu, and Shuo Li (2018), Glioma Segmentation Using a Novel Unified Algorithm in Multimodal MRI Images. IEEE Access, 6:9543-9554.

  136.     Zhifan Gao, Yanjie Li, Yuanyuan Sun, Jiayuan Yang, Huahua Xiong, Heye Zhang, Xin Liu, Wanqing Wu, Dong Liang, and Shuo Li (2018), Motion Tracking of the Carotid Artery Wall Motion From the Ultrasound Image Sequences: a Nonlinear State-space Approach. IEEE Transaction on Medical Imaging (TMI), 37: 273-283.

  137.     Wufeng Xue, Gary Brahm, Sachin Pandey, Stephanie Leung, and Shuo Li (2018), Full Left Ventricle Quantification via Deep Multitask Relationships Learning. Medical Image Analysis (MedIA), 43: 54-65.

  138.     Wufeng Xue, Ali Islam, Mousumi Bhaduri, and Shuo Li (2017), Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning. IEEE Transaction on Medical Imaging (TMI), 36:2057-2067.

  139.     Xiantong Zhen, Heye Zhang, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (2017), Direct and Simultaneous Estimation of Cardiac Four Chamber Volumes by Multioutput Sparse Regression. Medical Image Analysis (MedIA), 36:184-196.

  140.     Xiaoxu He, Heye Zhang, Manas Sharma, Gary Brahm, Ashley Mercado, and Shuo Li (2017), Unsupervised Boundary Delineation of Spinal Neural Foramina using A Multi-feature and Adaptive Spectral Segmentation. Medical Image Analysis (MedIA), 36:22-24.

  141.     Xiaoxu He, Andrea Lum, Manas Sharma, Gary Brahm, Ashley Mercado, and Shuo Li (2017), Automated Segmentation and Area Estimation of Neural Foramina with Boundary Regression Model. Pattern Recognition, 63:625-641

  142.     Zhongyi Han, Benzheng Wei, Yuanjie Zheng, Yilong Yin, Kejian Li, and Shuo Li (2017), Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model. Scientific Report, Article number: 4172.

  143.     Xiantong Zhen, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (2017), Descriptor Learning via Supervised Manifold Regularization for Multi-output Regression. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 28: 2035-2047.

  144.     Yunliang Cai, Andrea Lum, Ashley Mercado, Mark Landis, James Warrington, and Shuo Li (2017), Unsupervised Shape Discovery using Synchronized Spectral Networks. Pattern Recognition (PR), 69:39-51.

  145.     Guotao Liu, Yanping Zhang, Zhenghui Hu, Xiuquan Du, Wanqing Wu, Chenchu Xu, Xiangyang Wang, and Shuo Li, Complexity Analysis of Electroencephalogram Dynamics in Patients with Parkinson’s Disease, Parkinson’s Disease, vol. 2017, Article ID 8701061, 9 pages, 2017.

  146.     Zhifan Gao, Huahua Xiong, Heye Zhang, Xin Liu, Dhanjoo Ghistad, Wanqing Wu, and Shuo Li (2017), Robust Estimation of Carotid Artery Wall Motion Using the Elasticity-based State-space Approach. Medical Image Analysis (MedIA), 37:1-21.

  147.     Chenchu Xu, Zhifan Gao, Yanping Zhang, Heye Zhang, Xiuquan Du, Wanqing Wu, Lin Xu, Jiangming Huang, Huahua Xiong, Guotao Liu, and Shuo Li (2017), Beat-to-beat Blood Pressure and Two Dimensional (Axial and Radial) Motion of the Carotid Artery Wall: Physiological Evaluation of Arterial Stiffness. Scientific Report, Article number: 42254, doi:10.1038/srep42254.

  148.     Xiantong Zhen, Mengyang Yu, Feng Zheng, Ilanit Ben Nachum, David Laidley, and Shuo Li (2018), Multi-Target Sparse Latent Regression. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 29:1575-1586.

  149.     Guoyan Zheng, Chengwen Chu, Bulat Ibragimov, Robert Korez, Tomaz Vrtovec, Hugo Hutt, Richard Everson, Judith Meakin, Isabel Lsopez Andrade, Ben Glocker, Hao Chen, Qi Dou, Pheng-Ann Heng, Chunliang Wang, Daniel Forsberg, Ales Neubert, Jurgen Fripp, Martin Urschler, Darko Stern, Maria Wimmer, Alexey A. Novikov, Daniel L. Belavy, Hui Cheng, Gabriele Armbrecht, Dieter Felsenberg, and Shuo Li (2017), Evaluation and Comparison of 3D Intervertebral Disc Localization and Segmentation Methods for 3D T2 MR Data: A Grand Challenge. Medical Image Analysis (MedIA), 35:327-344.

  150.     Brandon Miles, Ismail Ben Ayed, Parsa Hojjat, Michael Wang, Aaron Fenster, Shuo Li, and Greg Garvin (2017), Spine Labeling in Axial Magnetic Resonance Imaging via Integral Kernels. Computerized Medical Imaging and Graphic (CMIG), 54:27-34

  151.     Lin Xu, Zekun Cai, Meihua Xiong, Yekuo Li, Guoying Li, Yu Deng, William Kongto Hau, Shuo Li, Wenhua Huang, and Jian Qiu (Dec. 2016), Efficacy of an Early Home-based Cardiac Rehabilitation Program for Patients After Acute Myocardial Infarction: A Three-dimensional Speckle Tracking Echocardiography Randomised Trial. Medicine, 95:e5638.

  152.     Bin Gu, Victor Sheng, Kengyeow Tay, Walter Romano, and Shuo Li (2017), Cross Validation Through Two-dimensional Solution Surface for Cost-Sensitive SVM. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 39:1103-1121.

  153.     Yunliang Cai, David Laidley, Anat Kornecki, Olga Shmuilovich, Andrea Lum, and Shuo Li (2016), Multi-Modal Vertebrae Recognition using Transformed Deep Convolution Network. Computerized Medical Imaging and Graphic (CMIG), 51:11-19.

  154.     Yunliang Cai, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (Sept. 2016), Unsupervised Freeview Groupwise Cardiac Segmentation using Synchronized Spectral Network. IEEE Transaction on Medical Imaging (TMI), 35: 2174-2188.

  155.     Jianhua Yao, Joseph E. Burns, Daniel Forsberg, Alexander Seitel, Abtin Rasoulian, Purang Abolmaesumi, Kerstin Hammernik, Martin Urschler, Bulat Ibragimov, Robert Korez, Tomaž Vrtovec, Isaac Castro-Mateos, Jose M. Pozo, Alejandro F. Frangi, Ronald M. Summers, and Shuo Li (2016), A Multi-center Milestone Study of Clinical Vertebral CT Segmentation, Computerized Medical Imaging and Graphics (CMIG), 49:16-28.

  156.     Kumaradevan Punithakumara, Ismail Ben Ayed, Mariam Afshin, Aashish Goela, Ali Islam, Shuo Li, Pierre Boulanger, Harald Becher, and Michelle Noga (2016), Detecting Left Ventricular Impaired Relaxation in Cardiac MRI using Moving Mesh Correspondences. Computer Methods and Programs in Biomedicine, 124:58-66.

  157.     Xiantong Zhen, Zhijie Wang, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (May 2016), Multi-Scale Deep Networks and Regression Forests for Direct Bi-ventricular Volume Estimation. Medical Image Analysis (MedIA), 30: 120-129.

  158.     Shuo Li, Jianhua Yao, and Nassir Navab (Aug. 2015), Guest Editorial: Special Issue on Spine Imaging, Image-Based Modeling, and Image Guided Intervention. IEEE Transaction on Medical Imaging (TMI), 34(8).

  159.     Guoyan Zheng, and Shuo Li (2015), Medical Image Computing in Diagnosis and Intervention of Spinal Diseases. (Invited perspective) Computerized Medical Imaging and Graphics (CMIG), 45:99-101.

  160.     Zhijie Wang, Xiantong Zhen, Keng Yeow Tay, Said Osman, Walt Romano, and Shuo Li (Aug. 2015), Regression Segmentation for M3 Spine Segmentation. IEEE Transaction on Medical Imaging (TMI), 34(8): 1640-8.

  161.     Ismail Ben Ayed, Kumaradevan Punithakumar, and Shuo Li (Sep. 1, 2015), Distribution Matching with the Bhattacharyya Similarity: a Bound Optimization Framework. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 37(9): 1777-1791.

  162.     Bin Gu, Victor S. Sheng, Zhijie Wang, Derek Ho, Said Osman, and Shuo Li (Jul. 2015), Incremental Learning for v-Support Vector Regression. Neural Networks (NN), 67:140-50.

  163.     Zhijie Wang, Mohamed Ben Salah, Bin Gu, Ali Islam, Aashish Goela, and Shuo Li (Apr. 2014), Direct Estimation of Cardiac Biventricular Volumes With an Adapted Bayesian Formulation. IEEE Trans. Biomedical Engineering (TBME), 61(4): 1251-1260.

  164.     Bin Gu, Victor Sheng, Kengyeow Tay, Walter Romano, and Shuo Li (July. 2015), Incremental Support Vector Learning for Ordinal Regression. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 26(7): 1403-1416.

  165.     Mariam Afshin, Ismail Ben Ayed, Kumaradevan Punithakumar, Max W. K. Law, Ali Islam, Aashish Goela, Terry M. Peters, and Shuo Li (Feb. 2014), Regional Assessment of Cardiac Left Ventricular Myocardial Function via MRI Statistical Features. IEEE Transactions on Medical Imaging (TMI), 33(2): 481-494.

  166.     Brandon Miles, Ismail Ben Ayed, Max Law, Gregory Garvin, Aaron Fenster, and Shuo Li (Jul. 2013), Spine Image Fusion via Graph Cuts. IEEE Trans. Biomedical Engineering (TBME), 60(7): 1841-1850.

  167.     Kumaradevan Punithakumar, Ismail Ben Ayed, Ali Islam, Ian Ross, and Shuo Li (Apr. 2013), Regional Heart Motion Abnormality Detection: an Information Theoretic Approach. Medical Image Analysis (MedIA), 17(3): 311-24.

  168.     Max Law, KengYeow Tay, Andrew Leung, Gregory Garvin, and Shuo Li (Jan. 2013), Intervertebral Disc Segmentation in MR Images using Anisotropic Oriented Flux. Medical Image Analysis (MedIA), 17(1): 43-61.

  169.     Kumaradevan Punithakumar, Jing Yuan, Ismail Ben Ayed, Shuo Li, and Yuri Boykov (Dec. 2012), A Convex Max-Flow Approach to Distribution Based Figure-Ground Separation. SIAM Journal on Imaging Sciences, 5(4), 22.

  170.     Ismail Ben Ayed, Hua-mei Chen, Kumaradevan Punithakumar, Ian Ross, and Shuo Li (Jan. 2012), Max-flow Segmentation of the Left Ventricle by Recovering Subject-specific Distributions via a Bound of the Bhattacharyya Measure. Medical Image Analysis (MedIA), 16(1): 87-100.

  171.     Kumaradevan Punithakumar, Ismail Ben Ayed, Ali Islam, Ian Ross, and Shuo Li (Aug. 2010), Tracking Endocardial Motion via Multiple Model Filtering. IEEE Transactions on Bio-medical Engineering (TBME), 57(8): 2001-2010.

  172.     Kumaradevan Punithakumar, Ismail Ben Ayed, Ian Ross, Ali Islam, Jaron Chong, and Shuo Li (Jul. 2010), Detection of Left Ventricular Motion Abnormality via Information Measures and Bayesian Filtering. IEEE Transactions on Information Technology in Biomedicine (TITB), 14(4): 1106-13.

  173.     Ismail Ben Ayed, Shuo Li, and Ian Ross (Dec. 2009), Embedding Overlap Priors in Variational Left Ventricle Tracking. IEEE Trans. Medical Imaging (TMI), 28(12): 1902-13.

  174.     Ismail Ben Ayed, Shuo Li, Ian Ross, and Ali Islam (Jan. 2009), Myocardium Tracking via Matching Distributions. International Journal of Computer Assisted Radiology and Surgery (IJCARS), 4(1): 37-44.

  175.     Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, and Song Li (Oct. 2007), Semi-automatic Computer Aided Lesion Detection in Dental X-rays using Variational Level Set. Pattern Recognition Journal, 40(10): 2861-2873.

  176.     Chao Jin, Thomas Fevens, Shuo Li, and Sudhir Mudur (Sep. 2007), Motion Learning-Based Framework for Unarticulated Shape Animation. The Visual Computer, 23(9-11): 753-761.

  177.     Shuo Li, Xiaoqing Liu, Jagath Samarabandu, Ian Ross, Greg Garvin, and Richard Rankin (Mar. 2006), A Fast and Robust Full Automatic Clinical System for Cardiac Functional Analysis on 4D and 5D MRI. International Journal on Computer Assisted Radiology and Surgery (IJCARS), 79-81.

  178.     Shuo Li, Chao Jin, Thomas Fevens, Adam Krzyzak, and Sudhir P. Mudur (Mar. 2006), A Medical Volume Reconstruction Method using Tetrahedral Meshes and Level Set. International Journal on Computer Assisted Radiology and Surgery (IJCARS), 61-63.

  179.     Shuo Li, Thomas Fevens, Adam Krzyzak, and Song Li (Mar. 2006), A Triple Region Image Segmentation Using Two Level Set Functions. International Journal on Computer Assisted Radiology and Surgery (IJCARS), 67-69.

  180.     Shuo Li, Thomas Fevens, Adam Krzyzak, and Song Li (Mar. 2006), An Automatic Variational Level Set Segmentation Framework for Computer Aided Dental X-Rays Analysis in Clinical Environments. Computerized Medical Imaging and Graphics (CMIG), 30(2): 65-74,

  181.     Shuo Li, Thomas Fevens, Adam Krzyzak, and Song Li (Mar. 2006), Automatic Clinical Image Segmentation using Pathological Modelling. Journal of Engineering Applications in Artificial Intelligence, 19(2), 65-74.

  182.     Shuo Li, Thomas Fevens, Adam Krzyzak, and Song Li (Mar. 2006), An Autonomous Level Set Segmentation for Computer Aided Dental X-ray Analysis. Computerized Medical Imaging and Graphics (CMIG), 30(2), 65-74.


Conference Papers 124 total:

Top conferences (~30% acceptance rate) we usually publish: AAAI Conference on Artificial Intelligence (AAAI), International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Information Processing in Medical Imaging (IPMI), Computer Vision and Pattern Recognition (CVPR), European Conference on Computer Vision (ECCV).

  1. Yunbo Shao (high school student), and Shuo Li (Feb. 2024), Adaptive Loss Engine for X-Ray Segmentation (ALEXS) for scoliosis intervention: assess digital segmentation and angle approximation (oral presentation). SPIE Conference on Medical Imaging, San Diego, California, United State

  2. Joshua Freeze, Ammar Hoori, Prerna Singh, Tao Hu, Robert Gilkeson, Sadeer Al-Kindiand, Shuo Li, and David L. Wilson (Feb. 2024), Prediction of heart failure using an analysis of epicardial adipose tissue from CT calcium score images. SPIE Conference on Medical Imaging, San Diego, California, United State

  3. Ammar Hoori, Joshua Freeze, Prerna Singh, Tao Hu, Hao Wu, Juhwan Lee, Shuo Li, Robert Gilkeson, Sadeer Al-Kindiand, Sanjay Rajagopalan, and David L. Wilson (Feb. 2024), Prediction of major adverse cardiovascular events using comprehensive AI analysis of calcifications and fat depots in CT calcium score images. SPIE Conference on Medical Imaging, San Diego, California, United State

  4. Zhen Li, Wen-Qian Yue, Gui-Bin Bian, Shuai Zhang, Wei-Peng Liu, Shuo Li, Elias Paulino Medeiros, Wan-Qing Wu, Victor Albuquerque (2023), A Dynamic-Static Weighted Network with Diverse-Token Fusion Attention for Rhexis Margin Recognition in Microscopic Surgery. 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO), Samui, Thailand.

  5. Pengzhong Sun, Wei Wang, Xiangyu Li, Suyu Dong, Gongning Luo, Kuanquan Wang, and Shuo Li (2023), Synergistically Learning Class-specific Tokens for Multi-class Whole Slide Image Classification. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), San Diego, California, United State

  6. Jianfeng Zhao, and Shuo Li (Oct. 2023), Learning Reliability of Multi-Modality Medical Images for Tumor Segmentation via Evidence-Identified Denoising Diffusion Probabilistic Models. 25rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada

  7. Bin Huang, Ziyue Xu, Shing-Chow Chan, Zhong Liu, Huiying Wen, Chao Hou, Qicai Huang, Meiqin Jiang, Changfeng Dong, Jie Zeng, Ruhai Zou, Bingsheng Huan, Xin Chen, and Shuo Li (Oct. 2023), A Style Transfer-based Augmentation Framework for Improving Segmentation and Classification Performance across Different Sources in Ultrasound Images. 25rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada

  8. Qikun Zhu, Qian Tang, Yanqing Wang, Lei Yin, Yanxiang Cheng, and Shuo Li (Oct. 2023), DCAug: Domain-aware & Content-consistent Cross-cycle Framework for Tumor Augmentation. 25rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada

  9. Xiaofei Chen, Yuting He, Cheng Xue, Rongjun Ge, Shuo Li, and Guanyu Yang (Oct. 2023), Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training. 25rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada

  10.   Yuting He, Guanyu Yang, Rongjun Ge, Yang Chen, Jean-Louis Coatrieux, Boyu Wang, and Shuo Li (June 2023), Geometric Visual Similarity Learning in 3D Medical Image Self-Supervised Pre-training, Computer Vision and Pattern Recognition Conference (CVPR), Vancouver, Canada

  11.   Zhenyu Wu, Lin Wang, Wei Wang, Qing Xia, Chenglizhao Chen, Aimin Hao, and Shuo Li (2023), Pixel is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection. AAAI 2023 Conference, Washington DC, USA

  12.   Zhenyu Wu, Lin Wang, Wei Wang, Tengfei Shi, Chenglizhao Chen, Aimin Hao, and Shuo Li (2022), Synthetic Data Supervised Salient Object Detection. ACM Multimedia 2022, Lisbon, Portugal

  13.   Rongjun Ge, Yuting He, Yang Chen, Shuo Li, and Daoqiang Zhang (2022), DDPNet: A novel dual-domain parallel network for low-dose CT reconstruction. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  14.   Xiaoming Qi, Guanyu Yang, Yuting He, Wangyan Liu, Ali Islam, and Shuo Li (2022), Contrastive Re-localization and History Distillation in Federated CMR Segmentation. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  15.   Yuqiang Gao, Guanyu Yang, Xiaoming Qi, Yinsu Zhu, and Shuo Li (2022), SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-Sequence MRI Diagnosis. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  16.   Jiacheng Shi, Yuting He, Youyong Kong, Juzheng Miao, Jean-Louis Coatrieux, Huazhong Shu, Guanyu Yang, and Shuo Li (2022), Full Transformer for Deformable Image Registration via Cross Attention. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  17.   Qikui Zhu, Yanqing Wang, Fei Liao, Jiancheng Yang, Lei Yin, and Shuo Li (2022), SelfMix: A Self-adaptive Data Augmentation Method for Lesion Segmentation. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  18.   Xiangyu Li, Xinjie Liang, Kuanquan Wang, Gongning Luo, Wei Wang, and Shuo Li (2022), ULTRA: Uncertainty-aware Label Distribution Learning for Breast Tumor Cellularity Assessment. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  19.   Liang Dong, Liu Jun, Xiaopu He, Kuanquan Wang, Gongning Luo, Wei Wang, and Shuo Li (2022), Position-prior Clustering-based Self-attention Module for Knee Cartilage Segmentation. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  20.   Kaini Wang, Yuting He, Shuaishuai Zhuang, Juzheng Miao, Xiaopu He, Ping Zhou, Guanyu Yang, Guangquan Zhou, and Shuo Li (2022), FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  21.   Chenchu Xu, Dong Zhang, Yuhui Song, Leonardo Kayat Bittencourt, Sree Harsha Tirumani, and Shuo Li (2022), Contrast-free Liver Tumor Detection using Ternary Knowledge Transferred Teacher-student Deep Reinforcement Learning. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore

  22.   Zhangfu Dong, Yuting He, Xiaoming Qi, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Guanyu Yang, and Shuo Li (2022), MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation. The 31st International Joint Conference on Artificial Intelligence (IJCAI-22), Vienna, Austria

  23.   Yuting He, Rongjun Ge, Jiasong Wu, Jean-Louis Coatrieux, Huazhong Shu, Yang Chen, Guanyu Yang, and Shuo Li (2022), Thin Semantics Enhancement via High-Frequency Priori Rule for Thin Structures Segmentation. IEEE International Conference on Data Mining (ICDM), Virtual

  24.   Jianfeng Zhao, Xiaojiao Xiao, Dengwang Li, Jaron Chong, Zahra Kassam, Bo Chen, and Shuo Li (2021), mfTrans-Net: Quantitative Measurement of Hepatocellular Carcinoma via Multi-Function Transformer Regression Network. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France

  25.   Song Wang, Yuting He, Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Jean-Louis Dillenseger, Jean-Louis Coatrieux, Guangyu Yang, and Shuo Li (2021), CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France

  26.   Lei Li, Shen Lian, Zhiming Luo, Shaozi Li, Beizhan Wang, and Shuo Li (2021), Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation. 24rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France

  27.   Zhiyuan Zhu, Boyu Wang, and Shuo Li (June 2021), A Triple-pooling Graph Neural Network for Multi-scale Topological Learning of Brain Functional Connectivity: Application to ASD Diagnosis, CAAI International Conference on Artificial Intelligence, Hangzhou, P.R.China. Best Student Paper

  28.   Yuting He, Rongjun Ge, Xiaoming Qi, Guanyu Yang, Yang Chen, Youyong Kong, Huazhong Shu, Jean-Louis Coatrieux, and Shuo Li (June 2021), EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation, 27th International Conference on Information Processing in Medical Imaging (IPMI), Rønne, Denmark

  29.   Fabio Accorsi, Yanan Ruan, Timothy Miao, Tyler Cossetto, Ian Chan, Omar Daher, Dengwang Li, Harry Marshall, Shuo Li, and Aashish Goela (Dec. 2020), Multi-tasking feature-sharing generative adversarial network for segmentation, tumor index quantification and uncertainty estimation of renal masses on CT, Annual Meeting of Radiological Society Of North America (RSNA), Virtual, Chicago, Illinois, USA.

  30.   Yuting He, Guanyu Yang, Tiantian Li, Huazhong Shu, Yang Chen, Youyong Kong, Jean-Louis Coatrieux, Jean-Louis Dillenseger, and Shuo Li (Aug. 2020), Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images, 16th European Conference on Computer Vision (ECCV), Glasgow, United Kingdom

  31.   Rongchang Zhao, Xuanlin Chen, Zailiang Chen, and Shuo Li (Aug. 2020), EGDCL: An Adaptive Curriculum Learning Framework for Unbiased Glaucoma Diagnosis, 16th European Conference on Computer Vision (ECCV), Glasgow, United Kingdom

  32.   Hongrong Wei, Heng Cao, Yiqin Cao, Yongjin zhou, Wufeng Xue, Dong Ni, and Shuo Li (Oct. 2020), Temporal-consistent Segmentation of Echocardiography with Co-learning from Appearance and Shape, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru

  33.   Yanan Ruan, Dengwang Li, Harry Marshall, Timothy Miao, Tyler Cossetto, Ian Chan, Omar Daher, Fabio Accorsi, Aashish Goela, and Shuo Li (Oct. 2020), Mt-UcGAN: Multi-task Uncertainty-constrained GAN for Joint Segmentation, Quantification and Uncertainty Estimation of Renal Tumors on CT, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru

  34.   Jiawei Huang, Haotian Shen, Bo Chen, Yue Wang, and Shuo Li (Oct. 2020), Segmentation of Paraspinal Muscles at Varied Lumbar Spinal Levels by Explicit Saliency-Aware Learning, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru

  35.   Heyou Chang, Shen Zhao, Hao Zheng, and Shuo Li (Oct. 2020), Multi-vertebrae Segmentation from Arbitrary Spine MRI Images under Global View, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru

  36.   Shen Zhao, Bin Chen, Heyou Chang, Xi Wu, and Shuo Li (Oct. 2020), Discriminative Dictionary-embedded Network for Comprehensive Vertebrae Tumor Diagnosis, 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru

  37.   Bangming Gong, Lu Shen, Cai Chang, Shichong Zhou, Weijun Zhou, and Shuo Li, and Jun Shi (Feb. 2020), Bi-Modal Ultrasound Breast Cancer Diagnosis via Multi-View Deep Neural Network SVM, 2020 IEEE International Symposium on Biomedical Imaging (ISBI), IOWA, USA

  38.   Chengqian Zhao, Cheng Feng, Dengwang Li, and Shuo Li (Feb. 2020), OF-MSRN: Optical Flow-Auxiliary Multi-Task Regression Network for Direct Quantitative Measurement, Segmentation and Motion Estimation, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York City, USA

  39.   Shen Zhao, Xi Wu, Bo Chen, and Shuo Li (Oct. 2019), Automatic Vertebrae Recognition from Arbitrary Spine MRI images by a Hierarchical Self-calibration Detection Framework, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  40.   Xiaojiao Xiao, Jarong Chong, Juanjuan Zhao, Yan Qiang, and Shuo Li (Oct. 2019), Radiomics-guided GAN for Segmentation of Liver Tumor without Contrast Agents, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  41.   Rongjun Ge, Yang Chen, Limin Luo, Guanyu Yang, Chen Feng, and Shuo Li (Oct. 2019), Stereo-Correlation and Noise-Distribution Aware ResVoxGAN for Dense Slices Reconstruction and Noise Reduction in Thick Low-Dose CT, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  42.   Zhifan Gao, and Shuo Li (Oct. 2019), Context-Aware Inductive Bias Learning for Vessel Border Detection in Multi-modal Intracoronary Imaging, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  43.   textbfYuting He, Guanyu Yang, Yang Chen, Youyong Kong, Jiasong Wu, Lijun Tang, Xiaomei Zhu, Jean-Louis Dillenseger, Huazhong Shu, Jean-Louis Coatrieux, Pengfei Shao, Shaobo Zhang, and Shuo Li, (Oct. 2019), DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  44.   Rongchang Zhao, Zailiang Chen, Xiyao Liu, Beiji Zou, and Shuo Li, (Oct. 2019), Multi-Index Optic Disc Quantification via MultiTask Ensemble Learning, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  45.   Gongning Luo, Suyu Dong, Kuanquan Wang, Dong Zhang, Yue Gao, Xin Chen, Henggui Zhang, and Shuo Li, (Oct. 2019), A Deep Reinforcement Learning Framework for Frame-by-frame Plaque Tracking on Intravascular Optical Coherence Tomography Image, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  46.   Ming Li, Weiwei Zhang, Guang Yang, Chengjia Wang, Heye Zhang, Huafeng Liu, Wei Zheng, and Shuo Li, (Oct. 2019), Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  47.   Dong Zhang, Guang Yang, Shu Zhao, Yanping Zhang, Heye Zhang, and Shuo Li, (Oct. 2019), Direct Quantification for Coronary Artery Stenosis Using Multiview Learning, 22th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China

  48.   Rongchang Zhao, Wangmin Liao, Beiji Zou, Zailiang Chen, and Shuo Li, (Jan. 2019), Weakly-Supervised Simultaneous Evidence Identification and Segmentation for Automated Glaucoma Diagnosis, The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA

  49.   Shumao Pang, Qianjing Feng, Stephanie Leung, Ilanit Ben Nachum, and Shuo Li, (Sept. 2018), Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network, 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain

  50.   Liansheng Wang, Xiuhao Xu, and Shuo Li, (2018), Utility Balanced Classification for Automatic Electronic Medical Record Analysis, 24th International Conference on Systems and Informatics (ICSAI), China.

  51.   Zhongyi Han, Benzheng Wei, Stephanie Leung, Jonathan Chung, and Shuo Li, (Sept. 2018), Towards Automatic Report Generation in Spine Radiology using Weakly Supervised Framework, 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain

  52.   Suyu Dong, Gongning Luo, Kuanquan Wang, Shaodong Cao, Ashley Mercado, Olga Shmuilovich, Henggui Zhang, and Shuo Li, (Sept. 2018), VoxelAtlasGAN: 3D Left Ventricle Segmentation on Echocardiography with Atlas Guided Generation and Voxel-to-voxel Discrimination, 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain

  53.   Wufeng Xue, Gary Brahm, Stephanie Leung, Ogla Shmuilovich, and Shuo Li, (Sept. 2018), Cardiac Motion Scoring with Segment- and Subject-level Non-Local Modeling, 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain

  54.   Sitong Wu, Zhifan Gao, Jianwen Luo, Zhi Liu, Heye Zhang, and Shuo Li, (Sept. 2018), Direct Reconstruction of Ultrasound Elastography Using an End-to-End Deep Neural Network, 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain

  55.   Chenchu Xu, Heye Zhang, Lei Xu, Gary Brahm, and Shuo Li, (Sept. 2018), MuTGAN: Simultaneous Segmentation and Quantification of Myocardial Infarction without Contrast Agents via Joint Adversarial Learning, 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain

  56.   Shizhong Dong, Zhifan Gao, Shanhui Sun, Xin Wang, Ming Li, Heye Zhang, Guang Yang, Huafeng Liu, and Shuo Li, (Sept. 2018), Holistic and Deep Feature Pyramids for Saliency Detection. British Machine Vision Conference (BMVC), Newcastle, UK

  57.   Min Li, Shizhong Dong, Kun Zhang, Zhifan Gao, Xi Wu, Heye Zhang, Guang Yang, and Shuo Li, (Sept. 2018), Deep Learning intra-image and inter-images features for Co-saliency detection. British Machine Vision Conference (BMVC), Newcastle, UK

  58.   Zongqing Ma, Xi Wu, Shanhui Sun, Chaoyang Xia, Zhipeng Yang, Shuo Li, and Jiliu Zhou, (April 2018), A Discriminative Learning Based Approach for Automated Nasopharyngeal Carcinoma Segmentation Leveraging Multi-Modality Similarity Metric Learning. IEEE International Symposium on Biomedical Imaging (ISBI), Washington DC, USA

  59.   Clara Tam, Xiaofeng Yang, Sibo Tian, X. Jiang, Johnathan J. Beitler, and Shuo Li (Feb. 2018), Automated Delineation of Organs-at-risk in Head and Neck CT Images using Multi-output Support Vector Regression. SPIE Conference on Medical Imaging, Houston, Texas, US

  60.   Wufeng Xue, Andrea Lum, Ashley Mercado, Mark Landis, James Warrington, and Shuo Li (Sept. 2017), Full Quantification of Left Ventricle via Deep Multitask Learning Network Respecting Intra- and Inter-Task Relatedness, 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec City, Canada

  61.   Chenchu Xu, Lei Xu, Zhifan Gao, Shen Zhao, Heye Zhang, Yanping Zhang, Xiuquan Du, Shu Zhao, Dhanjoo Ghista, and Shuo Li (Sept. 2017), Direct Detection Pixel-Level Myocardial Infarction Area via Deep-Learning Algorithm, 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec City, Canada

  62.   Hongbo Wu, Chris Bailey, Parham Rasoulinejad, and Shuo Li (Sept. 2017), Automatic Landmark Estimation for Adolescent Idiopathic Scoliosis Assessment using BoostNet, 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec City, Canada

  63.   Haoliang Sun, Xiantong Zhen, Yuanjie Zheng, Gongping Yang, Yilong Yin, and Shuo Li (June 2017), Learning Deep Match Kernels for Image-Set Classification, Computer Vision and Pattern Recognition (CVPR), Honolulu, USA

  64.   Wufeng Xue, Ilanit Ben Nachum, Sachin Pandey, James Warrington, Stephanie Leung, and Shuo Li (June 2017), Direct Estimation of Regional Wall Thicknesses via Residual Recurrent Neural Network, The 25th biennial international conference on Information Processing in Medical Imaging (IPMI), Boone, USA

  65.   Haoliang Sun, Xiantong Zhen, Chris Bailey, Parham Rasoulinejad, Yilong Yin, and Shuo Li, (June 2017), Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression, The 25th international conference on Information Processing in Medical Imaging (IPMI), Boone, USA

  66.   Shengran Su, Zhifan Gao, Heye Zhang, Qiang Lin, William Kongto Hau, and Shuo Li (April 2017), A Detection of Lumen and Media-Adventitia Borders in Ivus Images using Sparks Auto-Encoder Neural Network. IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia

  67.   Liansheng Wang, Shusheng Li, Yiping Chen, Jiankun Lin, Changhua Liu, Xiantong Zeng, and Shuo Li (April 2017), Direct Aneurysm Volume Estimation by Multi-View Semi-Supervised Manifold Learning. IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia

  68.   Clara Tam, Xiaoxu He, Manas Sharma, Ashley Mercado, Mark Landis, and Shuo Li (Dec. 2017), Automated Multi-Vertebrae and Disc Delineation for MR and CT Spinal Images. Annual Meeting of Radiological Society Of North America (RSNA), Chicago, Illinois, USA.

  69.   Xiaoxu He, Andrea Lum, Ashley Mercado, Mark Landis, James Warrington, and Shuo Li (Feb. 2017), Automated Grading of Lumbar Disc Degeneration via Supervised Distance Metric Learning. SPIE Conference on Medical Imaging, Orlando, Florida, US

  70.   Yunliang Cai, Stephanie Leung, James Warrington, Sachin Pandey, Olga Shmuilovich, and Shuo Li (Feb. 2017), Direct Spondylolysis Identification and Spondylolisthesis Measurement in MR/CT using Detectors Trained by Articulated Parameterized Spine Model. SPIE Conference on Medical Imaging, Orlando, Florida, US

  71.   Liansheng Wang, Shusheng Li, and Shuo Li (Feb. 2017), Volume Calculation of CT Lung Lesions Based on Halton Low-Discrepancy Sequences. SPIE Conference on Medical Imaging, Orlando, Florida, US

  72.   Xiangrong Zhou, Takuya Kano, Shuo Li, Xinin Zhou, Takeshi Hara, and Hiroshi Fujita (Feb. 2017), Automated Assessment of Breast Tissue Density in Non-Contrast 3d CT Images Without Image Segmentation Based on a Deep CNN. SPIE Conference on Medical Imaging, Orlando, Florida, US

  73.   Xiantong Zhen, Yilong Yin, Mousumi Bhaduri, Ilanit Ben Nachum, David Laidley, and Shuo Li (Oct. 2016), Multi-Task Shape Regression for Medical Image Segmentation. Medical Image Computing and Computer-Assisted Intervention (MICCAI), Athens, Greece.

  74.   Xiaoxu He, Yilong Yin, Manas Sharma, Gary Brahm, Ashley Mercado, and Shuo Li (Oct. 2016), Automated Diagnosis of Neural Foraminal Stenosis Using Synchronized Superpixels Representation. Medical Image Computing and Computer-Assisted Intervention (MICCAI), Athens, Greece.

  75.   Zhifan Gao, Huahua Xiong, Yuanyuan Sun, Xin Liu, Heye Zhang, Yaoqin Xie, Dhanjoo Ghista, Wanqing Wu, Yanjie Li, and Shuo Li (Oct. 2016), Carotid Artery Wall Motion Estimated from Ultrasound Imaging Sequences Using a Nonlinear State Space Approach. Medical Image Computing and Computer-Assisted Intervention (MICCAI), Athens, Greece.

  76.   Xiaoxu He, Andrea Lum, Manas Sharma, Olga Shmuilovich, Gary Brahm, and Shuo Li (Dec. 2016), First Computer-Aided Diagnosis of Neural Foramina Stenosis. Annual Meeting of Radiological Society Of North America (RSNA), Chicago, Illinois, USA.

  77.   Liansheng Wang, Shusheng Li, Xiantong Zhen, Changhua Liu, Mousumi Bhaduri, Ashley Mercado, and Shuo Li (Dec. 2016), Clinical Validation of Direct Volume Estimation for Left Atrial Aneurysm. Annual Meeting of Radiological Society Of North America (RSNA), Chicago, Illinois, USA.

  78.   Shuo Li, Andrea Lum, Gary Brahm, Ilanit Ben Nachum, Manas Sharma, Olga Shmuilovich, and James Warrington (Oct. 2016), A Bag-of-Shapes Descriptor for Medical Imaging. The 23rd IEEE International Conference on Image Processing (ICIP), Phoenix Convention Centre, Phoenix, Arizona, USA.

  79.   Xiangrong Zhou, Takuya Kano, Yunliang Cai, Shuo Li, Xinin Zhou, Takeshi Hara, Ryujiro Yokoyama, and Hiroshi Fujita (Feb. 2016), Automatic Quantification of Mammary Glands on Non-Contrast X-Ray Ct by Using a Novel Segmentation Approach. In Proc. of SPIE Medical Imaging, San Diego CA, USA.

  80.   Xiantong Zhen, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (Oct. 2015), Direct and Simultaneous Four-Chamber Volume Estimation by Multi-Output Regression. Medical Image Computing and Computer-Assisted Intervention (MICCAI), Munich, Germany

  81.   Yunliang Cai, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (Oct. 2015), Unsupervised Free-view Groupwise Segmentation for M3 Cardiac Images using Synchronized Spectral Network. Medical Image Computing and Computer-Assisted Intervention (MICCAI), Munich, Germany

  82.   Xiantong Zhen, Zhijie Wang, Mengyang Yu, and Shuo Li (Jun. 2015), Supervised Descriptor Learning for Multi-Output Regression. Computer Vision and Pattern Recognition (CVPR), pp. 1211-1218, Boston, USA

  83.   Bin Gu, Victor S. Sheng, and Shuo Li (Jul. 2015), Bi-Parameter Space Partition for Cost-Sensitive SVM. International Joint Conferences on Artificial Intelligence (IJCAI), 3532-3539, Buenos Aires, Argentina

  84.   Xiaoxu He, Jaron Chong, Said Osman, Manas Sharma, Mark Landis, and Shuo Li (Dec. 2015), Automated delineation of neural foramina from spine images. Annual Meeting of Radiological Society of North America (RSNA), Chicago, Accepted, U.S.A

  85.   Shuo Li, Amy Lin, Keng Yeow Tay, Walter Romano, and Said Osman (Feb. 2015), Prognosis of Intervertebral Disc Loss From Diagnosis of Degenerative Disc Disease. SPIE Conference on Medical Imaging, Vol. 9414, Orlando, Florida, USA

  86.   Xiantong Zhen, Zhijie Wang, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (Feb. 2015), Direct Volume Estimation Without Segmentation. SPIE Conference on Medical Imaging, Orlando, Florida, USA

  87.   Kumaradevan Punithakumar, Michelle Noga, Pierre Boulanger, Ismail Ben Ayed, Mariam Afshin, Aashish Goela, Ali Islam, and Shuo Li (2014), Detecting Left Ventricular Impaired Relaxation Using Mr Imaging. IEEE-EMBS International Conference on BHI (Biomedical and Health Informatics), 210-313. Spain

  88.   Xiantong Zhen, Zhijie Wang, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (Dec. 2014), A Comparative Study of Methods for Cardiac Ventricular Volume Estimation. 100th Annual Meeting of Radiological Society of North America (RSNA), Chicago, USA

  89.   Zhijie Wang, Mohamed Ben Salah, Ismail Ben Ayed, Ali Islam, Aashish Goela, Shuo Li (Dec. 2013), Bi-ventricular Volume Estimation for Cardiac Functional Assessment. 99th Annual Meeting of Radiological Society of North America (RSNA), Chicago, United States

  90.   Xiantong Zhen, Zhijie Wang, Ali Islam, Mousumi Bhaduri, Ian Chan, and Shuo Li (Sep. 2014), Direct Estimation of Cardiac Bi-ventricular Volumes with Regression Forests. Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp:586-593, Boston, USA

  91.   Max W. K. Law, Gregory Garvin, Sudhakar Tummala, KengYeow Tay, Andrew Leung, and Shuo Li (Jun. 2013), Gradient Competition Anisotropy for Centerline Extraction and Segmentation of Spinal Cords. Information Processing in Medical Imaging (IPMI), pp: 49-61, Asilomar, California, USA

  92.   Max W. K. Law, KengYeow Tay, Andrew Leung, Gregory Garvin, and Shuo Li (Oct. 2012), Dilated Divergence based Scale-Space Representation for Curve Analysis. European Conference on Computer Vision (ECCV), pp: 557-571, Firenze, Italy

  93.   Mariam Afshin, Ismail Ben Ayed, Ali Islam, Aashish Goela, Ian G. Ross, Terry M. Peters, and Shuo Li (May. 2012), Estimation of the Cardiac Ejection Fraction from Image Statistics. 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp: 824-827, Barcelona, Spain

  94.   Brandon Miles, Max W. K. Law, Ismail Ben Ayed, Greg Garvin, Aaron Fenster, and Shuo Li (Feb. 2012), Pixel Level Image Fusion for Medical Imaging: An Energy Minimizing Approach. SPIE Medical Imaging 2012: Computer-Aided Diagnosis, San Diego, California, USA

  95.   Mariam Afshin, Ismail Ben Ayed, Ali Islam, Aashish Goela, Terry M. Peters, and Shuo Li (Sep. 2012), Global Assessment of Cardiac Function Using Image Statistics in MRI. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 15(2):535-43, Nice, France

  96.   Kumaradevan Punithakumar, Ismail Ben Ayed, Ali Islam, Aashish Goela, and Shuo Li (Sept. 2012), Regional Heart Motion Abnormality Detection via Multiview Fusion. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 15(2):527-534, Nice, France

  97.   Mariam Afshin, Ismail Ben Ayed, Kumaradevan Punithakumar, Max W. K. Law, Ali Islam, Aashish Goela, Ian G. Ross, Terry M. Peters, and Shuo Li (Sep. 2011), Myocardial Function via Statistical Features in MR Images. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp: 107-114, Toronto, Canada

  98.   Ismail Ben Ayed, Kumaradevan Punithakumar, Gregory Garvin, Walter Romano, and Shuo Li (Jul. 2011), Graph Cuts with Invariant Object-Interaction Priors: Application to Intervertebral Disc Segmentation. 22nd International Conference on Information Processing in Medical Imaging (IPMI), pp:171-183, Monastery Irsee, Germany

  99.   M. S. Nambakhsh, Kumaradevan Punithakumar, Ismail Ben Ayed, Aashish Goela, Ali Islam, Terry Peters, and Shuo Li (Mar. 2011), A Neural Network Learned Information Measures for Heart Motion Abnormality Detection. Proc. SPIE 7962, SPIE Medical Imaging 2011: Image Processing, Orlando, Florida, USA

  100.     Mariam Afshin, Ismail Ben Ayed, Ali Islam, Ian Ross, Terry Peters, and Shuo Li (Mar. 2011), Variational Level-Set Segmentation and Tracking of Left Ventricle Using Field Prior. Proc. SPIE 7962, SPIE Medical Imaging 2011: Image Processing, Orlando, Florida, United States

  101.     Mohammad Saleh Nambakhsh, Jing Yuan, Ismail Ben Ayed, Kumaradevan Punithakumar, Aashish Goela, Ali Islam, Terry Peters, and Shuo Li (Jan. 2011), A Convex Max-Flow Segmentation of LV Using Subject-Specific Distributions on Cardiac MRI. Information processing in medical imaging (IPMI), 22:171-183, Kloster Irsee, Germany

  102.     Ismail Ben Ayed, Kumaradevan Punithakumar, Gregory Garvin, Walter Romano, and Shuo Li (Jan. 2011), Graph Cuts With Invariant Object-Interaction Priors: Application to Intervertebral Disc Segmentation. Information processing in medical imaging (IPMI), 22:221-32, Kloster Irsee, Germany

  103.     Hua-Mei Chen, Aashish Goela, Greg Garvin, and Shuo Li (Sep. 2010), Deformation Fields for Diffeomorphic Image Registration and Its Application to Myocardial Delineation. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 13(1):340-8, Beijing, China

  104.     Ismail Ben Ayed, Amar Mitiche, Mohamed Ben Salah, and Shuo Li, Finding Image Distributions on Active Curves (Jun. 2010). IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp: 3225-3232, San Francisco, USA

  105.     Ismail Ben Ayed, Hua-Mei Chen, Kumaradevan Punithakumar, Ian Ross and Shuo Li (Jun. 2010), Graph Cut Segmentation with a Global Constraint: Recovering Region Distribution via a Bound of the Bhattacharyya Measure. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp: 3288-3295, San Francisco, USA.

  106.     Kumaradevan Punithakumar, Ismail Ben Ayed, Ali Islam, Ian Ross, and Shuo Li (Oct. 2010), Regional Heart Motion Abnormality Detection via Information Measures and Unscented Kalman Filtering. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 13(1): 409-417, Beijing, China

  107.     Kumaradevan Punithakumar, Ismail Ben Ayed, Ian Ross, Ali Islam, and Shuo Li (Nov. 2009), Tracking Endocardial Boundary and Motion via Graph Cut Distribution Matching and Multiple Model Altering. The Ninth Asian Conference on Computer Vision (ACCV), Xi’an, China

  108.     Kumaradevan Punithakumar, Shuo Li,Ismail Ben Ayed, Ian Ross, Ali Islam, and Jaron Chong (Sep. 2009), Heart Motion Abnormality Detection via an Information Measure and Bayesian Filtering. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 12(2), pp: 373-80, Imperial College, London, United Kingdom

  109.     Ismail Ben Ayed, Kumaradevan Punithakumar, Shuo Li, Ali Islam, and Jaron Chong (Sep. 2009), Left Ventricle Segmentation via Graph Cut Distribution Matching. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 12(2), pp: 901-909, Imperial College London, United Kingdom

  110.     Ismail Ben Ayed, Shuo Li, and Ian Ross (Jun. 2009), Level Set Image Segmentation With a Statistical Overlap Constraint. Information processing in medical imaging (IPMI), 21:589-601, Williamsburg, United States

  111.     Ismail Ben Ayed, Shuo Li, and Ian Ross (Jun. 2008), Tracking Distributions With an Overlap Prior. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, USA

  112.     Ismail Ben Ayed, Shuo Li, Greg Garvin, and Rethy Chhem (Feb. 2008), Area Prior Constrained Level Set Evolution for Medical Image Segmentation. SPIE Conference on Medical Imaging, Proc. SPIE 6914, Medical Imaging 2008: Image Processing, San Diego, California, USA

  113.     Xiaoqing Liu, Jagath Samarabandu, Greg Garvin, Rethy Chhem, and Shuo Li (Feb. 2008), A Learning-Based Automatic Spinal Mri Segmentation. SPIE Conference on Medical Imaging, Medical Imaging 2008: Image Processing, San Diego, California, USA

  114.     Ismail Ben Ayed, Yingli Lu, Shuo Li, and Ian Ross (Mar. 2008), Left Ventricle Tracking Using Overlap Priors. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 11(1):1025-1033, New York, USA

  115.     Shuo Li, Ian Ross, Sukhdeep Gill, Terry Peters, and Richard Rankin (Feb. 2008), Computer Aided Septal Defect Diagnosis and Detection. SPIE Conference on Medical Imaging, Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65141A, San Diego, California, USA

  116.     Xiaoqing Liu, Jagath Samarabandu, Shuo Li, Ian Ross, and Greg Garvin (Feb. 2007), A Learning-based Automatic Clinical Organ Segmentation in Medical Images. SPIE Conference on Medical Imaging, San Diego, California, USA

  117.     Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, and Song Li (Mar. 2007), Computer Aided Root Decay Detection using Level Set and Complex Wavelets. SPIE Conference on Medical Imaging, Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, San Diego, California, USA

  118.     Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, and Song Li (Oct. 2006), Fast and Robust Clinical Triple-Region Image Segmentation Using One Level Set Function. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 9(2): 766-73, Copenhagen, Denmark

  119.     Shuo Li, Thomas Fevens, Adam Krzyzak, Chao Jin, and Song Li (Oct. 2005), Toward Automatic Computer Aided Dental X-Ray Analysis Using Level Set Method. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 8(1): 670-8, Palm Springs, USA

  120.     Shuo Li, Thomas Fevens, Adam Krzyzak, and Song Li (Jul. 2005), SVM in Clinical Image Segmentation with Pathological Model. International Conference on Machine Learning and Data Mining (MLDM) in Pattern Recognition, pp: 314-324, Leipzig, Germany

  121.     Shuo Li, Thomas Fevens, Adam Krzyzak, and Song Li (Feb. 2005), Level Set Segmentation for Computer Aided Dental X-ray Analysis. SPIE conference on Medical Imaging, Proc. SPIE 5747, Medical Imaging 2005: Image Processing, pp: 580-589, San Diego, California, USA

  122.     Chao Jin, Thomas Fevens, Shuo Li, and Sudhir P. Mudur (Apr. 2005), Feature Preserving Volumetric Data Simplification for Application in Medical Imaging. International conference in Central Europe on Computer Graphics, pp: 235- 242, Plzen, Czech Republic

  123.     Shuo Li, Thomas Fevens and Adam Krzyzak (Sep. 2004), Image Segmentation Adapted for Clinical Settings by Combining Pattern Classification and Level Sets. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp: 160-167, St. Malo, France

  124.     Shuo Li, Thomas Fevens, and Adam Krzyzak (Sep. 2004) An SVM based Framework for Autonomous Volumetric Medical Image Segmentation Using Hierarchical and Coupled Level Sets. Computer Aided Radiology and Surgery (CARS), pp: 207-212, Illinois, Chicago, USA


Patents

  1. Shuo Li, Contrast-Agent-Free Medical Diagnostic Imaging, US Patent Application Number: 17/138353, 2020. https://patents.google.com/patent/US11837354B2/en

  2. Shuo Li, Yungliang Cai, Said Osman, Mark Landis, Manas Sharma, Multi-modality vertebra recognition, Application Number: US 14/701,769, 2015.

  3. Shuo Li, Walter Romano, Kengyeow Tray, Said Osman, Systems and methods for a predictive intervertebral disc degeneration detection engine, Application Number: #61/925755, 2014.

  4. Shuo Li, Ian Ross, Richard Rankin, Methods and apparatus to process left-ventricle cardiac images, Publication Numbers: US8229192 B2, CN102177527A, US20100040270, WO2010019334A1, Publication Date: Jul 24, 2012. http://www.google.com/patents/US8229192

  5. Shuo Li, Prakash Mahesh, Dave Roeder, Ian Ross, Systems and methods for computer aided analysis of images, Publication Numbers: US8121364 B2, US8224052, US20090316964, US20120106823, Publication Date: Feb 21, 2012. http://www.google.ca/patents/US8121364

  6. Shuo Li, Ismail Ben Ayed, Ian Ross, Richard Rankin, Systems and methods for tracking images, Publication Numbers: US8144930 B2, US20100135529, Publication Date: Mar 27, 2012. http://www.google.com/patents/US8144930

  7. Shuo Li, Prakash Mahesh, Dave Roeder, Richard Rankin, System and method for image based multiple-modality cardiac image alignment, Publication Numbers: US8165361 B2, US8639060, US20090180675, US20120170823, Publication Date: Apr 24, 2012. http://www.google.com/patents/US8165361

  8. Shuo Li, Ismail Ben Ayed, Ian Ross, Richard Rankin, Systems and methods for tracking images, Publication Numbers: US8144930 B2, US20100135529, Publication Date: Mar 27, 2012. http://www.google.com/patents/US8144930


Social Media

Google Scholar: https://scholar.google.ca/citations?user=6WNtJa0AAAAJ&hl=en

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