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电子科技大学机械与电气工程学院导师教师师资介绍简介-王国泰

本站小编 Free考研考试/2021-09-12


王国泰副教授
所在系所: 机械工程系
出生年月: 1989年10月
导师代码:
电子邮件: guotai.wang@uestc.edu.cn
通讯地址: 清水河校区主楼C1-501
个人主页: http://faculty.uestc.edu.cn/wangguotai/


教育经历 资源 1ldpi
2014-2018 伦敦大学学院(UCL),医学与生物医学影像,博士
2011-2014 上海交通大学,生物医学工程,硕士
2009-2011 上海交通大学,智能科学与技术,第二专业学士
2007-2011 上海交通大学,生物医学工程,学士


工作经历 资源 1ldpi
2018.10-至今 电子科技大学,机械与电气工程学院,副教授
2018.7-2018.9 伦敦国王学院,生物医学工程学院,研究助理
2018.1-2018.7 伦敦大学学院,医学物理与生物医学工程系,研究助理

研究方向 资源 1ldpi
1、医学图像计算
2、深度学习
3、计算机视觉


研究项目与课题 资源 1ldpi
2014-2017 英国Engineering and Physical Science Research Council (EPSRC)项目:Image segmentation for fetal surgery planning, No. **,主研。
2012-2014 国家自然科学基金面上项目:基于组合稀疏轮廓先验模型和最小监督分类的肝脏割及手术规划关键理论研究,No. **, 主研。


代表性学术成果 资源 1ldpi
近年来,以第一作者身份发表SCI或EI索引论文12篇,包括在人工智能及医学图像领域的顶级期刊IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, 影响因子17.73)、Medical Image Analysis (影响因子8.88)、IEEE Transactions on Medical Imaging (TMI, 影响因子7.82)等上发表的多篇论文,并申请国内专利3项,国际专利一项。主要论文成果如下:
期刊论文:
1.Guotai Wang*, Maria A Zuluaga, Wenqi Li, Rosalind Pratt, Premal A Patel, Michael Aertsen, Tom Doel, Anna L Divid, Jan Deprest, Sebastien Ourselin, Tom Vercauteren. DeepIGeoS: A deep interactive geodesic framework for medical image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol 41(7), pp 1559-1572, 2019.
2.Guotai Wang*, Wenqi Li, Michael Aertsen, Jan Deprest, Sébastien Ourselin, Tom Vercauteren. Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks. Neurocomputing, vol 338, pp 34-45, 2019.
3.Guotai Wang*, Wenqi Li, Maria A Zuluaga, Rosalind Pratt, Premal A Patel, Michael Aertsen, Tom Doel, Anna L David, Jan Deprest, Sebastien Ourselin, Tom Vercauteren. Interactive medical image segmentation using deep learning with image-specific fine-tuning. IEEE Transactions on Medical Imaging, vol 37(7), pp 1562-1573, 2018.
4.Guotai Wang*, Maria A Zuluaga, Rosalind Pratt, Michael Aertsen, Tom Doel, Maria Klusmann, Anna L David, Jan Deprest, Tom Vercauteren, Sebastien Ourselin. Slic-Seg: A minimally interactive segmentation of the placenta from sparse and motion-corrupted fetal MRI in multiple views. Medical Image Analysis, vol 34, pp 137-147, 2016.
5.Guotai Wang, Shaoting Zhang, Hongzhi Xie, Dimitris N. Metaxas and Lixu Gu*. A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning. Medical Image Analysis, vol 19, pp 176-186, 2015.
会议论文:
1.Michael Ebner*, Guotai Wang*, Wenqi Li, Michael Aertsen, Premal A. Patel, Rosalind Aughwane, Andrew Melbourne, Tom Doel, Anna L. David, Jan Deprest, Sebastien Ourselin, and Tom Vercauteren. An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI. In Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 313-320, 2018. (共同第一作者)
2.Guotai Wang*, Wenqi Li, Sebastien Ourselin and Tom Vercauteren. Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks. In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, pp 179-190, 2018. (2017年MICCAI脑肿瘤分割挑战赛第二名)
3.Guotai Wang*, Maria A. Zuluaga, Rosalind Pratt, Michael Aertsen, Tom Doel, Maria Klusmann, Anna L. David, Jan Deprest, Tom Vercauteren and Sébastien Ourselin. Dynamically Balanced Online Random Forests for Interactive Scribble-based Segmentation. In Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 352-360, 2016.
4.Guotai Wang*, Maria A. Zuluaga, Rosalind Pratt, Michael Aertsen, Anna L. David, Jan Deprest, Tom Vercauteren and Sébastien Ourselin. Slic-Seg: Slice-by-slice segmentation propagation of the placenta in fetal MRI using one-plane scribbles and online learning. In Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 29-37, 2015.
5.Guotai Wang, Shaoting Zhang and Lixu Gu*, Scalable Sparse Shape Composition and Its Application to Liver Surgical Planning. IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp 377-380, 2014.



荣誉与奖励 资源 1ldpi


招生专业 资源 1ldpi
硕士招生专业
080200机械工程
06方向: 机器人技术



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