杨冠羽

发布者:杨发布时间:2019-01-03浏览次数:15969

杨冠羽

副院长

教授 博士生导师

影像科学与技术系主任

  

计算机科学与工程学院 影像科学与技术系

医学信息处理江苏省国际合作联合实验室

中法生物医学信息研究中心(Centre de Recherche en Information Biomédicale Sino-Français (CRIBs)

江苏南京四牌楼2号东南大学群贤楼2204

Tel025 - 83794249

Emailyang.list(AT)seu.edu.cn

  

主要研究方向:深度学习、医学人工智能、计算机辅助智能诊断、计算机辅助智能手术、医学图像分析

东南大学生物医学工程专业本科(2002),硕士(2005)、法国雷恩一大信号与图像处理专业博士(2008)、荷兰莱顿大学医学中心(LUMCLeiden University)图像处理实验室博士后(2009-2011年).2011年回国后进入东南大学任教。现为计算机科学与工程学院副院长、教授、博士生导师、影像科学与技术系主任2018年任中国图象图形学学会医学影像专业委员会委员,IEEE高级会员。

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,(2018ZX10201-002-003,子课题负责人,2018-2021

  • 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,(2242019K3DN08,东大负责人,2019-2020

  • 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(61828101,国内主要合作人,2019-2020

  • 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,(2017YFC0107903,主要参与,2017-2019

  • 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(81101104,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(31571001,主持,2016 - 2019

  • 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(BK2012743,主持,2013 - 2015

  • 东南大学优秀青年教师教学科研项目(A类资助,2016 - 2018

科研获奖

  • 教育部自然科学奖二等奖,基于正交变换的信号与图像处理方法研究,2012,排名第4

  • 江苏省医学科技奖二等奖,低剂量CT血管造影在主动脉夹层腔内治疗筛选和预防判断中的应用,2017,排名第5

  • 江苏省科学技术三等奖,基于标准化染色的细胞病理学智能诊断整体解决方案及其应用,2018,排名第4


发表论文

期刊论文:

He, Y.T., Li, T.T., Ge, R. J., Yang, J., Kong, Y.Y, Shu, H.Z, Yang, G.Y.(*), Li, S(*)., Few-Shot Learning for Deformable Medical Image Registration With Perception-Correspondence Decoupling and Reverse Teaching, IEEE Journal of Biomedical and Health Informatics, 10.1109/JBHI.2021.3095409.

He, Y.T., Yang, G.Y.(*), Yang, J., Ge, R. J., Kong, Y.Y, Zhu, X.M., Zhang, S.B., Shao, P.F.,  Shu, H.Z, Dillenseger, J-L., Coatrieux J-L., Li, S.(*) Meta grayscale adaptive network for 3D integrated renal structures segmentation. Medical Image Analysis, 2021, 71: 102055.  (医学图像处理国际顶级期刊,中科院一区)

He, Y.T., Yang, G.Y.(*), Yang, J., Chen, Y., Kong, Y.Y, Wu, J.S., Tang, L.J., Zhu X.M.,  Dillenseger, J-L., Shao, P.F., Zhang, S.B., Shu, H.Z, Coatrieux J-L., Li, S.. “Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.” Medical Image Analysis, 2020, 63: 101722. (医学图像处理国际顶级期刊,中科院一区)

Ge, R.J.(#), Yang, G.Y.(#), Chen, Y. (*), Luo, L.M., Feng, C., Ma, H., Ren, J.Y., Li, S. (*). “K-Net: Integrate Left Ventricle Segmentation and Direct Quantification of Paired Echo Sequence.” IEEE Transactions on Medical Imaging, 2020,39(5):1690-1702.(医学图像处理国际顶级期刊,中科院一区)

Yang G.Y. (#), Lv T. L(#)., Shen Y.P., Li S., Yang J. (*), Chen Y. (*), Shu H.Z., Luo L.M., Coatrieux J.L.. Vessel Structure Extraction using Constrained Minimal Path Propagation . Artificial Intelligence in Medicine, 105:101846. (JCR Q1, IF=4.38) 

Ge, R.J.(#), Yang, G.Y., Chen, Y. (*), Luo, L.M., Feng, C., Zhang, H.Y., Li, S. (*). “PV-LVNet: Direct Left Ventricle Multitype Indices Estimation from 2D Echocardiograms of Paired Apical Views with Deep Neural Networks.” Medical Image Analysis, 2019, 58: 101554. (医学图像处理国际顶级期刊,中科院一区)

Wang, T.T., Xu, Y., Liu, W.Y., Shao, P.F., Lv, Q., Yang, G. (*), Tang, L.J. (*), Measurement of Glomerular Filtration Rate Using Multiphasic Computed Tomography in Patients With Unilateral Renal Tumors: A Feasibility Study. Frontiers in Physiology, 2019, 10:1209.  (JCR Q2, IF=4.13) 

Lv, T.L., Yang, G.,Zhang, YD., Yang J, Chen Y(*), Shu, H., Luo, L.M.. (2019)Vessel segmentation using centerline constrained level-set method. Multimedia Tools and Applications. 2019, 78(12):17051-75..

Zhang, S.B.(#), Yang, G(#), Tang, L.J.(#), Lv, Q., Li, J., Xu, Y., Zhu, X.M., Li, P., Shao, P.F.(*), Wang, Z.,(2018) Application of a functional three-dimensional perfusion model in laparoscopic partial nephrectomy with precise segmental renal artery clamping. Urology, 125:98-103.

Cao, Q., Broersen, A., Graaf, M. A. D., Kitslaar, P. H., Yang, G., Scholte, A. J., Lelieveldt, B.P.F., Reiber, J.H.C., Dijkstra, J. (*).(2017)Automatic identification of coronary tree anatomy in coronary computed tomography angiography. The International Journal of Cardiovascular Imaging, 2017, 33(11), 1809-1819.

Yang, G.*, Chen, Y., Sun, Q., Ning, X., Shu, H., Coatrieux, J. L. (2016)Fully Automatic Coronary Calcification Detection in Non-Contrast CT Images. Medical Physics, 43(5):2174-2186.

Wolterink, J. M.(*), Leiner, T., De Vos, B. D., Coatrieux, JL., Kelm, B. M., Kondo, S., Salgado RA. Shahzad R., Shu H., Snoeren M. Takx RA. Van Vliet LJ. Van Walsum T., Willems TP., Yang G., Zheng YF., Viergever MA., Išgum I..(2016)An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework. Medical Physics, 2016, 43(5): 2361-2373.

Liu, W.Y.(#), Zhu, Y.S. (#), Tang, L.J., Zhu, X.M., Xu, Y. (*), Yang, G.(*) .(2016)Effect of various environments and computed tomography scanning parameters on renal volume measurements in vitro: A phantom study. Experimental and Therapeutic Medicine, 12: 753-758.

Yang, G.*, Lalande, V., Chen, L., Azzabou, N., Larcher, T., Certaines, J.D., Shu, H., Coatrieux, J. L. (2015) MRI texture analysis of GRMD dogs using orthogonal moments: A preliminary study. IRBM 36:213-219

Li, B., Yang, G., Coatrieux, J. L, Li, B., Shu, H*. (2015). 3D nonrigid medical image registration using a new information theoretic measure. Physics in Medicine and Biology, 60: 8767-90.

Yu, G*, Liang, Y., Yang, G., Shu, H., Li, B., Yin, Y., Li, D. (2015) Accelerated gradient-based free form deformable registration for online adaptive radiotherapy. Physics in Medicine and Biology. 60: 2765-83

Zhu, X.#, Zhu, Y.#, Xu, H., Wan, Y., Choo, K. S., Yang, G., Tang, L.*, Xu, Y.* (2014). An individualized contrast material injection protocol with respect to patient-related factors for dual-source CT coronary angiography. Clinical radiology, 69(2), e86-e92.

粟华、杨冠羽、胡轶宁、舒华忠*,基于相位的C-V模型乳腺超声图像分割方法,东南大学学报(自然科学版), 43(3), pp494-497, 2013年 5月

Xu, Y.#, Shao, P.#, Zhu, X., Lv, Q., Liu, W., Xu, H., Zhu, Y., Yang, G., Tang, L.*, Yin, C.*. (2013). Three-dimensional renal CT angiography for guiding segmental renal artery clamping during laparoscopic partial nephrectomy.Clinical radiology, 68(11), e609-e616.

Chen, Y.*, Yang, Z., Hu, Y., Yang, G., Zhu, Y., Li, Y. Toumoulin, C. (2012). Thoracic low-dose CT image processing using an artifact suppressed large-scale nonlocal means. Physics in Medicine and Biology,57(9), 2667.

Wu, J.*, Wang, L., Yang, G., Senhadji, L., Luo, L., Shu, H. (2012). Sliding conjugate symmetric sequency-ordered complex Hadamard transform: fast algorithm and applications, IEEE Transactions on Circuits and Systems I: Regular Papers,59(6), 1321-1334.

Yang, G.*, Kitslaar, P., Frenay, M., Broersen, A., Boogers, M. J., Bax, J. J., Reiber, J. H. C., Dijkstra, J. (2012). Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography.The international journal of cardiovascular imaging,28(4), 921-933.

Yang, G.*, Zhou, J., Boulmier, D., Garcia, M. P., Luo, L., Toumoulin, C. (2010). Characterization of 3-D coronary tree motion from MSCT angiography. IEEE Transactions on Information Technology in Biomedicine, 14(1), 101-106.


 会议论文:

He, Y.T., Ge, R.J., Wu J.S., Coatrieux, J-L, Shu, H.Z., Chen, Y,, Yang, G.Y.(*) and Li, S. Thin Semantics Enhancement via High-Frequency Priori Rule for Thin Structures Segmentation. International Conference on Data Mining (ICDM2021), Auckland, New Zealand, Dec., 7-10, 2021, Accepted. (数据挖掘国际顶会,CCF B类会议)

Wang, S., He, Y.T., Kong, Y.Y, Zhu, X.M., Zhang, S.B., Shao, P.F., Dillenseger, J-L., Coatrieux J-L., Li, S., Yang, G.Y.(*), CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation, Medical Image Computing and Computer Assisted Interventions (MICCAI2021), online, Sept. 27-Oct.1, 2021. (医学图像处理国际顶级会议)

Zhao, Z.T., Yang, G.Y.(*) ,Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification, Medical Image Computing and Computer Assisted Interventions (MICCAI2021), online, Sept. 27-Oct.1, 2021. (医学图像处理国际顶级会议)

He, Y.T., Ge, R.J., Qi X.M., Yang, G.Y.(*), Chen, Y, Kong, Y.Y, Shu, H.Z., Coatrieux, J-L, and Li, S. EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation. IPMI2021, online. 2021.6.28-7.2. (医学影像分析顶会)

He, Y.T., Li, T.T., Yang, G.Y.(*), Kong, Y.Y, Chen, Y, Shu, H.Z, 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. (计算机视觉国际顶会,CCF B类会议)

He, Y.T., Yang, G. (*), Chen, Y., Kong, Y.Y., Wu, J.S., Tang L.J., Zhu, X.M., Dillenseger, J-L., Shao, P.F., Zhang, S.B., Shu, H.Z., 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.

Lu, Z.W., Yang, G. (*), Hua, T.C., Hu, L.Y., Kong, Y.Y., Tang L.J., Zhu, X.M., Dillenseger, J-L., Shu, H.Z., 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.

Pan, T., Yang, G. (*), Wang, C.X., Zhou, Z.W., Kong, Y.Y., Tang L.J., Zhu, X.M., Dillenseger, J-L., Shu, H.Z., 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, Taibei, 2019.9.22-25.

Zhao, X.R., Yang, G. (*), Chen, Y., Lv, T.L., Sun, W.Y., Shu, H., 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.

Zhang C., Yang, G. (*),Shu, H., Liu, Y.N., Wen, Y.G., 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.

Yang, G.(*), Li, G.Q., Pan, T., Kong, Y.Y., Wu, J.S., Shu, H., Luo, L.M., Dillenseger, J.L., Coatrieux, J.L., Tang, L.J., Zhu, X.M.. 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), 2018.8.20-2018.8.24.

Yang, G.*, Chen, Y., Tang, L., Shu, H., Toumoulin, C. (2014, April). Automatic left ventricle segmentation based on multiatlas registration in 4D CT images. InBiomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on(pp. 413-416). IEEE.

Yang, G.*, Chen, Y., Sun, Q., Ning, X., Shu, H., Coatrieux, J. L. Fully Automatic Coronary Calcification Detection in Non-Contrast CT Images. Proceedings of Automatic Coronary Calcium Scoring Challenge on MICCAI2014, 2014/9/14-2014/9/18,

Li, B., Yang, G., Shu, H.*, Coatrieux, J. L. (2014, August). A New Divergence Measure Based on Arimoto Entropy for Medical Image Registration. InPattern Recognition (ICPR), 2014 22nd International Conference on(pp. 3197-3202). IEEE.

Chen, Y.*, Cao, Q., Yang, G., Shu, H., Luo, L., Toumoulin, C., Coatrieux, J. L. (2014, April). Centerline constrained minimal path propagation for vessel extraction. InBiomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on (pp. 794-797). IEEE.

Yang, G.*, Broersen, A., Petr, R., Kitslaar, P., de Graaf, M. A., Bax, J. J., Reiber, J.H.C.Dijkstra, J. (2011, September). Automatic coronary artery tree labeling in coronary computed tomographic angiography datasets. In Computing in Cardiology, CinC2011 (pp. 109-112). IEEE.

授权专利及软著

杨冠羽、王征、伍家松、杨淳沨、舒华忠,一种冠状动脉CT造影图像钙化点检测方法,国家发明专利,专利号:CN201310307604.6,授权


杨冠羽、王征、宁秀芳、孙巧榆、舒华忠,一种全自动CT图像冠状动脉钙化分数计算方法,国家发明专利,专利号:CN201410356582.7,授权


杨冠羽宁秀芳、王征、舒华忠, 一种医学图像三维血管显示增强方法, 国家发明专利,2018.8.28,专利号:ZL201510844775.1,授权.


三维Zernike矩血管特征计算软件(3DZDVesselV1.0,主要完成人:顾金金,杨冠羽,登记号:2015SR193094,证书号:软著登字第1080180