杨冠羽
计算机科学与工程学院、软件学院、人工智能学院副院长
教授、博导
主要研究方向：图像处理与分析、深度学习、医学人工智能
东南大学计算机科学与工程学院、软件学院、人工智能学院副院长、教授、博士生导师，IEEE高级会员。中国图象图形学会医学影像专业委员会委员。东南大学生物医学工程专业博士（2008）、法国雷恩一大信号与图像处理专业博士（2009）、荷兰莱顿大学医学中心（LUMC，Leiden University）图像处理实验室博士后。长期从事医学人工智能、图像处理与分析、计算机辅助诊断与手术方面的研究。承担及参与国家重点研发计划、国家科技重大专项、国家自然科学基金、江苏省自然科学基金等项目十余项。发表包括IEEE TIP、IEEE TMI、IEEE JBHI、Med Image Anal、CVPR、IJCAI、MICCAI等顶级期刊和会议在内的论文60余篇，授权国家发明专利12项。曾获得教育部自然科学二等奖（2012）、江苏省医学科技奖二等奖（2017）、江苏省科学技术三等奖（2018）等奖项。
科研项目
· 国家科技重大专项，艾滋病和病毒性肝炎等重大传染病防治，面向高维大数据的手足口病暴发流行和重症病例预测预警模型构建与应用，（子课题负责人，2018-2021）
· 国家自然科学基金海外及港澳学者合作研究基金，心脏CT图像“一站式”诊断平台中图像处理关键算法研究（国内主要合作人，2019-2020）
· 国家自然科学基金青年基金项目，CCTA图像冠状动脉自动分割算法研究（主持，2012 - 2014）
· 国家自然科学基金面上项目，肾部分切除手术中图像处理关键技术研究（主持，2016 - 2019，61万）
· 江苏省自然科学基金面上项目，冠状动脉CT造影图像处理关键问题研究（主持，2013 - 2015）
· 国家“数字诊疗装备研发”重点研发计划课题，DSA混合引导支架实时精确定位，（主要参与，2017-2019）
· 东南大学-南京医科大学合作项目，基于肾周脂肪的多组学融合特征分析用于原发性高血压分型与精准治疗的研究，（东大负责人，2019-2020）
· 东南大学优秀青年教师教学科研项目（A类资助，2016 - 2018）
近期主要科研成果
Publications (* represents (co-)corresponding author, # represents co-first author)
Journal Papers:
ü Yang GY*, He YT, Lv Y, Chen Y, Coatrieux JL, Sun XX, Wang Q, Wei, YY, Li S, Zhu YS*. 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 (IEEE-JBHI), 2023, 27(4): 1967-1978.
ü Jiang ZY, He YT, Ye S, Shao PF, Zhu XM, Xu Y, Chen Y, Coatrieux JL, Li S, Yang GY*. O2M-UDA: Unsupervised dynamic domain adaptation for one-to-multiple medical image segmentation. Knowledge-Based Systems, 2023, 265: 110378.
ü Gao Y, Xin L, Lin H, Yao B, Zhang T, Zhou AJ, Huang S, Wang JH, Feng YD, Yao SH, Guo Y, Dang T, Meng XM, Yang ZZ, Jia WQ, Pang HF, Tian XJ, Deng B, Wang JP, Fan WC, Wang J, Shi LH, Yang GY, Sun C, Wang W, Zang JC, Li SY, Shi RH, Li ZS*,Wang LW*. Machine learning-based automated sponge cytology for screening of oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction: a nationwide, multicohort, prospective study, The Lancet Gastroenterology & Hepatology, 2023, 8(5): 432-445.
ü He YT, Ge RJ, Qi XM, Chen Y, Wu JS, Coatrieux JL, Yang GY*, S Li. Learning Better Registration to Learn Better Few-Shot Medical Image Segmentation: Authenticity, Diversity, and Robustness. IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), 2022, online.
ü Kong JD, He YT, Zhu XM, Shao PF, Xu Y, Chen Y, Coatrieux JL, Yang GY *. BKC-Net: Bi-Knowledge Contrastive Learning for renal tumor diagnosis on 3D CT images. Knowledge-Based Systems. 2022, 252:109369.
ü Qi XM, Yang GY*, Chen Y, Yang J, Liu WY, Zhu YS, Xu Y, Shu HZ, Li S*. MVSGAN: Spatial-aware Multi-view CMR Fusion for accurate 3D Left Ventricular Myocardium Segmentation, IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI), 2022, 26(5):2264-2275.
ü He YT, Li TT, Ge RJ, Yang J, Kong YY, Shu HZ, Yang GY*, Li S*, Few-Shot Learning for Deformable Medical Image Registration With Perception-Correspondence Decoupling and Reverse Teaching, IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI), 2022, 26(3):1177-1187.
ü Feng LL#, Liu ZY#, Li CF#, Li ZH#, Lou XY#, Shao LZ#, Wang YL, Huang Y, Chen HY, Pang XL, Liu S, He, F, Zheng J, Meng XC, Xie PY, Yang GY, Ding Y, Wei MB, Yun JP, Hung MC, Zhou WH, Wahl DR, Lan P, Tian J*, Wan XB*. Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multi-center observational study. The Lancet Digital Health. 2022. 4(1): e8-e17.
ü Ji TJ, Chen Q, Zhang Y, Zeng HR, Wang JX, Yang GY, Xu WB, Liu HT, A Novel Early Warning Model for Hand, Foot and Mouth Disease Prediction Based on a Graph Convolutional Network, Biomedical and Environmental Sciences, 2022, 35(6): 494-503.
ü Zhang SB#, Yang GY, Qian J, Zhu XM, Li J, Li P, He YT, Xu Y, Shao PF, Wang ZJ. A novel 3D deep learning model to automatically demonstrate renal artery segmentation and its validation in nephron-sparing surgery. Front Oncol. 2022 Oct 14; 12: 997911.
ü Kong JD, He YT, Zhu XM, Shao PF, Xu Y, Chen Y, Coatrieux JL, Yang GY*. BKC-Net: Bi-Knowledge Contrastive Learning for renal tumor diagnosis on 3D CT images. Knowledge-Based Systems. 2022, 252:109369
ü Qi YL#, Xu H#, He YT, Li GY, Li ZH, Kong YY, Coatrieux JL, Shu HZ, Yang GY*, Tu SX*, Examinee-Examiner Network: Weakly Supervised Accurate Coronary Lumen Segmentation Using Centerline Constraint”, IEEE Transactions on Image Processing (IEEE-TIP), 2021, 30: 9429-9441.
ü Shao LZ#, Liu ZY#, Yan Y#, Liu JG, Ye XJ, Xia HZ, Zhu XH, Zhang YT, Zhang ZY, Chen HY, He W, Liu C, Lu M, Huang Y, Sun K, Zhou XZ, Yang GY*, Lu J*, Tian J*. Patient-Level Prediction of Multi-Classification Task at Prostate MRI Based on End-to-End Framework Learning From Diagnostic Logic of Radiologists. IEEE Transactions on Biomedical Engineering (IEEE-TBME), 2021, 68(12):3690-3700.
ü He YT, Yang GY*, Yang J, Ge RJ, Kong YY, Zhu XM, Zhang SB, Shao PF, Shu HZ, Dillenseger JL., Coatrieux JL, Li S*. Meta grayscale adaptive network for 3D integrated renal structures segmentation. Medical Image Analysis(MedIA), 2021, 71: 102055
ü Zhang C, Shu HZ*,Yang GY, Li FQ, Wen YG, Zhang Q, Dillenseger JL, Coatrieux, JL, HIFUNet: Multi-Class Segmentation of Uterine Regions From MR Images Using Global Convolutional Networks for HIFU Surgery Planning, IEEE Transactions on Medical Imaging, 2020, 39(11):3309-3320.
ü He YT, Yang GY*, Yang J, Chen Y, Kong YY, Wu JS, Tang LJ, Zhu XM, Dillenseger JL, Shao PF, Zhang SB, Shu HZ, Coatrieux JL, Li S. “Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation. Medical Image Analysis (MedIA), 2020, 63: 101722.
ü Ge RJ#, Yang GY#, ChenY*, Luo LM, Feng C, Ma H, Ren JY, Li S*. K-Net: Integrate Left Ventricle Segmentation and Direct Quantification of Paired Echo Sequence. IEEE Transactions on Medical Imaging (IEEE-TMI), 2020，39(5):1690-1702.
ü Shao LZ#, Yan Y#, Liu ZY#, Ye XJ#, Xia HZ, Zhu XH, Zhang YT, Zhang ZY, Chen HY, He W, Liu C, Lu M, Huang Y, Ma LL, Sun K, Zhou XZ, Yang GY*, Lu J*, Tian J*. Radiologist-Like Artificial Intelligence for Grade Group Prediction of Radical Prostatectomy for Reducing Upgrading and Downgrading From Biopsy. Theranostics, 2020, 10(22): 10200 - 10212.
ü Yang GY#, Lv TL#, Shen YP, Li S, Yang J*, Chen Y*, Shu HZ, Luo LM, Coatrieux J-L. Vessel Structure Extraction using Constrained Minimal Path Propagation. Artificial Intelligence in Medicine, 2020, 105:101846.
ü Ge RJ, Yang GY, ChenY*, Luo LM, Feng C, Zhang HY, LiS*. PV-LVNet: Direct Left Ventricle Multitype Indices Estimation from 2D Echocardiograms of Paired Apical Views with Deep Neural Networks. Medical Image Analysis (MedIA), 2019, 58: 101554.
ü Wang TT, Xu Y, Liu WY, Shao PF, Lv Q, Yang GY*, Tang LJ*. Measurement of Glomerular Filtration Rate Using Multiphasic Computed Tomography in Patients With Unilateral Renal Tumors: A Feasibility Study. Frontiers in Physiology, 2019, 10:1209.
ü Lv TL, Yang GY,Zhang YD, Yang J, Chen Y*, Shu H, Luo, LM. Vessel segmentation using centerline constrained level-set method. Multimedia Tools and Applications, 2019, 78(12):17051-75.
ü Zhang SB#, Yang GY#, Tang LJ#, Lv Q, Li J, Xu Y, Zhu XM, Li P, Shao PF*, Wang Z, Application of a functional three-dimensional perfusion model in laparoscopic partial nephrectomy with precise segmental renal artery clamping. Urology, 125, 98-103, 2019.
ü Cao Q, Broersen A, Graaf MAD, Kitslaar PH, Yang GY, Scholte AJ, Lelieveldt BPF, Reiber JHC, Dijkstra J*.Automatic identification of coronary tree anatomy in coronary computed tomography angiography. The International Journal of Cardiovascular Imaging,2017, 33(11), 1809-1819.
ü Chen Y*, Zhang YD, Yang J, Cao Q, Yang GY, Chen J, Shu HZ, Luo LM, CoatrieuxJ-L, Feng QJ, Curve-like structure extraction using minimal path propagation with backtracking, IEEE Transactions on Image Processing, 2016, 25, 988-1003, 2016
ü Liu WY#, Zhu YS#, Tang LJ, Zhu XM, Xu Y*, Yang GY* .Effect of various environments and computed tomography scanning parameters on renal volume measurements in vitro: A phantom study. Experimental and Therapeutic Medicine, 2016, 12: 753-758.
ü Yang GY*, Chen Y, Sun Q, Ning X, Shu HZ, Coatrieux J-L. Fully Automatic Coronary Calcification Detection in Non-Contrast CT Images. Medical Physics, 2016, 43(5):2174-2186.
ü Wolterink JM*, Leiner T, De Vos BD, Coatrieux J-L, Kelm BM, Kondo S, Salgado RA, Shahzad R, Shu HZ, Snoeren M, Takx RA, Van Vliet LJ, Van Walsum T, Willems TP, Yang GY, Zheng YF, Viergever MA, Išgum I. An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework. Medical Physics, 2016, 43(5): 2361-2373.
ü Yang GY*, Lalande V, Chen L, Azzabou N, Larcher T, Certaines JD, Shu HZ, Coatrieux J-L MRI texture analysis of GRMD dogs using orthogonal moments: A preliminary study. IRBM 36:213-219, 2015
ü Li B, Yang GY, Coatrieux J-L, Li B, Shu HZ*. 3D nonrigid medical image registration using a new information theoretic measure.Physics in Medicine and Biology, 60: 8767-90, 2015
ü Yu G*, Liang Y, Yang GY, Shu HZ, Li B, Yin Y, Li D. Accelerated gradient-based free form deformable registration for online adaptive radiotherapy. Physics in Medicine and Biology60: 2765-83, 2015.
ü Yang GY*, Kitslaar P, Frenay M, Broersen A, Boogers M, Bax J, Reiber J, Jouke D. Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography.The International Journal of Cardiovascular Imaging.2012, 28(4), 921-933.
ü Yang GY*, Zhou J, Boulmier D, Garcia M-P, Luo LM, Toumoulin C, Characterization of 3-D Coronary Tree Motion from MSCT Angiography, IEEE Transactions on Information Technology in Biomedicine, 14(1), 2010, 101-106.
ü Bousse A*, Zhou J, Yang GY, Bellanger J-J, Toumoulin C, Motion Compensated Tomography Reconstruction of Coronary Arteries in Rotational Angiography, IEEE Transactions on Biomedical Engineering, 56(4), 2009, 1254–1257.
ü Yang GY, Shu HZ*, Toumoulin C, Han G, Luo LM, Efficient Legendre Moment Computation for Grey Level Images,Pattern Recognition, 39(1), 2006, pp.74-80.
Conference Proceedings:
ü Qi YL, He YT, Qi XM, Zhang Y, Yang GY*. Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentation, ICCV2023, Accepted.
ü Zhang Z, Zhang XL, Qi YL, Yang GY*. Partial Vessels Annotation-based Coronary Artery Segmentation with Self-training and Prototype Learning, MICCAI2023, Accepted.
ü Chen XF, He YT, Xue C, Ge RJ, Li S, Yang GY*. Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training, MICCAI2023, Accepted.
ü He YT, Yang GY*, Ge RJ, Chen Y, JL Coatrieux, BY Wang, Li S. Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training. CVPR 2023. Vancouver, Canada, June 18–22, 2023.
ü Qi XM, Yang GY*, He YT, Liu WY, Islam A, Li S. Contrastive Re-localization and History Distillation in Federated CMR Segmentation. MICCAI 2022, Singapore, Sept. 18–22, 2022.
ü Gao YQ, Yang GY*, Qi XM, Zhu YS, Li S. SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-Sequence MRI Diagnosis. MICCAI 2022, Singapore, Sept. 18–22, 2022.
ü Shi JC, He YT，Kong YY, Coatrieux JL, Shu HZ, Yang GY*, Li S. XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention. MICCAI 2022,Singapore, Sept. 18–22, 2022.
ü Dong ZF, He YT, Qi XM, Chen Y, Shu HZ, Coatrieux JL, Yang GY*, Li S. MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation. International Joint Conference on Artificial Intelligence (IJCAI) 2022. Messe Wien, Vienna, Austria, July 23-29, 2022.
ü He YT, Ge RJ, Wu JS, Coatrieux J-L, Shu HZ, Chen Y, Yang GY*, Li S. Thin Semantics Enhancement via High-Frequency Priori Rule for Thin Structures Segmentation. International Conference on Data Mining (ICDM), Auckland, New Zealand, Dec., 7-10, 2021.
ü Wang S, He YT, Kong YY, Zhu XM, Zhang SB, Shao PF, Dillenseger J-L, Coatrieux J-L, Li S, Yang GY*, CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation, MICCAI, online, Sept. 27-Oct.1, 2021.
ü Zhao ZT, Yang GY* ,Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification, MICCAI, online, Sept. 27-Oct.1, 2021.
ü HeYT, Ge RJ, Qi XM, Yang GY*, Chen Y, Kong YY, Shu HZ, Coatrieux J-L, Li S. EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation. IPMI 2021, online. 2021.6.28-7.2.
ü He YT, Li TT, Yang GY*, Kong YY, Chen Y, Shu HZ, Coatrieux J-L, Dillenseger J-L, Li S, Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images, ECCV 2020, Glasgow, 2020.8.23-28.
ü He YT, Yang GY*, Chen Y, KongYY, Wu JS, Tang LJ, Zhu XM, Dillenseger J-L, Shao PF, Zhang SB, Shu HZ, Coatrieux J-L, Li S, DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy, MICCAI 2019, Shenzhen, 2019.10.13-17.
ü Lu ZW, Yang GY*, Hua TC, H LY. KongYY, Tang LJ, Zhu XM, Dillenseger J-L, Shu HZ, Coatrieux J-L. Unsupervised Three-dimensional Image Registration using a Cycle Convolutional Neural Network., IEEE International Conference on Image Processing, ICIP2019, Taibei, 2019.9.22-25.
ü Pan T, Yang GY*, Wang CX, Zhou ZW, Kong YY, Tang LJ, Zhu XM, Dillenseger J-L, Shu HZ, Coatrieux J-L. A Multi-task Convolutional Neural Network for Renal Tumor Segmentation and Classification Using Multi-phasic CT Images, IEEE International Conference on Image Processing, ICIP2019, Taipei, China, Sept.22-25, 2019.
ü Zhao XR, Yang GY*, Chen Y, Lv TL, Sun WY, Shu HZ, Haigron P. Segmentation of aorta dissection CT images using convolution neural networks. In 33rd International Congress and Exhibition of Computer Assisted Radiology and Surgery (CARS 2019), Jun. 18-21, 2019, Rennes.
ü Zhang C, Yang GY*,Shu HZ, Liu YN, Wen YG, Zhang Q, Dillenseger J-L. Segmentation of uterus and uterine fibroids in MR images using convolutional neural networks for HIFU surgery planning. In 33rd International Congress and Exhibition of Computer Assisted Radiology and Surgery (CARS 2019), Jun. 18-21, 2019, Rennes.
ü YangGY*, Li GQ, Pan T, Kong YY, Wu JS, Shu HZ, Luo LM, Dillenseger J-L, Coatrieux J-L, Tang LJ, Zhu XM. Automatic Segmentation of Kidney and Renal Tumor in CT Images Based on 3D Fully Convolutional Neural Network with Pyramid Pooling Module. In 24th International Conference on Pattern Recognition (ICPR 2018), Beijing, China, Aug. 20-24, 2018.
