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万涛 博士
北京航空航天大学, 生物与医学工程学院, 副教授
Tao Wan, Ph.D. & Associate Professor
Email: taowan@buaa.edu.cn.
个人简介：
致力于研究基于人工智能方法的医学图像分析方法及计算机辅助诊断和预测系统的应用研究，从交叉学科的角度研究癌症与健康相关问题、开展医学图像分析、医疗大数据、医疗人工智能、计算病理学的关键技术研究；在国际学术期刊和会议共发表中英文学术论文80余篇，申请专利10余项，获批软件著作权2项。
研究方向:
基于乳腺癌/宫颈癌/脑肿瘤/肺癌/心血管疾病的计算机辅助诊断和预测系统；组织病理图像定量分析；多模态医学数据融合；医学图像处理；计算机视觉；机器学习；医学人工智能。
Research Interests:
Computer aided diagnosis and prognosis for breast cancer, cervical cancer, brain tumor, lung cancer, and cardiovascular diseases; Quantitative analysis of pathological images; Multimodal medical data fusion; Medical image processing; Computer vision; Machine learning, Medical AI.
教育经历：
2005/10-2009/05 英国布里斯托大学电气和电子工程系，电子与电气工程，博士
2002/09-2004/02 英国布里斯托大学计算机系，全球计算与多媒体，硕士
1996/09-2000/07 北京科技大学计算机系，计算机及应用，学士
Education：
2005/10-2009/05 University of Bristol, UK, Electronic and Electrical Engineering, Ph.D.
2002/09-2004/02 University of Bristol, UK, Global Computing and Multimedia, M.Sc.
1996/09-2000/07 University of Science and Technology, Beijing, Computer Science and Technology, B.Eng.
科研工作经历:
2013/09-至今 北京航空航天大学生物与医学工程学院，助理教授、副教授、博士生导师
2011/06-2013/08 美国波士顿大学医学中心/美国凯斯西储大学，博士后研究员
2010/12-2011/06 美国卡内基-梅隆大学机器人研究所，访问研究员
2009/07-2010/09 中国三星技术院，高级研究员
2008/09-2008/11 美国加州大学圣地亚哥分校，访问学者
2007/07-2007/08 希腊研究与技术基金会下属计算机科学学院，访问学者
Employment / Training：
2013/09 – Present Beihang University, Beijing, Assistant Professor & Associate Professor
2011/06-2013/08 Boston University School of Medicine/Case Western Reserve University, Postdoctoral Research Fellow
2010/12-2011/06 Carnegie Mellon University, USA, Visiting Researcher
2009/07-2010/09 Samsung Advanced Institute of Technology, China, Senior Researcher
2008/09-2008/11 University of California, San Diego, USA, Visiting Scholar
2007/07-2007/08 Foundation for Research and Technology (FORTH-ICS), Heraklion, Greece, Visiting Scholar
近期发表论文(Selected Recent Publications)：
1. Junyu Ji, Tao Wan, Dong Chen, Hao Wang, Menghan Zheng, Zengchang Qin, A deep learning method for automatic evaluation of diagnostic information from multi-stained histopathological images, Knowledge-Based Systems, 2022, 256:109820.
2. Yu Zhang, Yuqi Luo, Xin Kong, Tao Wan, Yunling Long and Jun Ma, A preoperative MRI-based radiomics-clinicopathological classifier to predict the recurrence of pituitary macroadenoma within 5 years, Frontiers in Neurology, 2022, 12:780628.
3. Tao Wan, Chunxue Wu, Ming Meng, Tao Liu, Chuzhong Li, Jun Ma, Zengchang Qin, Radiomic Features on Multiparametric MRI for Preoperative Evaluation of Pituitary Macroadenomas Consistency: Preliminary Findings, Journal of Magnetic Resonance Imaging, 2021, DOI: 10.1002/jmri.27930, 1-13.
4. Tao Wan, Jianhui Chen, Zhonghua Zhang, Deyu Li, Zengchang Qin. Automatic vessel segmentation in X-ray angiogram using spatio-temporal fully-convolutional neural network, Biomedical Signal Processing and Control, 2021, 68:102646.
5. Tao Wan, Lei Zhao, Hongxiang Feng, Deyu Li, Chao Tong, Zengchang Qin. Robust nuclei segmentation in histopathology using ASPPU-Net and boundary refinement, Neurocomputing, 2020, 408:144-156.
6. Tan Wan, Shusong Xu, Chen Sang, Yylan Jin, Zengchang Qin. Accurate segmentation of overlapping cells in cervical cytology with deep convolutional neural networks, Neurocomputing, 2019, 365:157-170.
7. Tao Wan, Hongxiang Feng, Chao Tong, Deyu Li, Zengchang Qin. Automated identification and grading of coronary artery stenosis with X-ray angiography, Computer Methods and Programs in Biomedicine, 2018, 167:13-22.
8. Tao Wan, Xiaoqing Shang, Weilin Yang, Jianhui Chen, Deyu Li, Zengchang Qin. Automated coronary artery tree segmentation in X-ray angiography using improved Hessian Based enhancement and statistical region merging, Computer Methods and Programs in Biomedicine, 2018, 157:179-190.
9. Tao Wan, Wanshu Zhang, Min Zhu, Jianhui Chen, Zengchang.Qin. Automated mitosis detection in histopathology based on non-Gaussian modeling of complex wavelet coefficients, Neurocomputing, 2017, 237:291-303.
10. Tao Wan, Jiajia Cao, Jianhui Chen, Zengchang Qin. Automated grading of breast cancer histopathology using cascaded ensemble with combination of multi-level image features, Neurocomputing, 2017, 229:34-44.
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