个人简介
高杨,男,中南大学计算机学院硕士生导师,澳大利亚University of Queensland 客座研究员(Honorary Fellow),2022年8月于澳大利亚昆士兰大学信息技术与电子工程学院(school of ITEE)获得博士学位,11月加入中南大学计算机学院工作。研究方向专注于新型快速高分辨率定量磁共振技术,尤其是定量磁化率(QSM)成像重建及分析技术,致力于构建新的影像快速采集和相关配套的AI驱动重建及分析技术。
获得澳大利亚昆士兰州政府资助全额博士奖学金(2018-2022),并在领域内权威学术期刊和会议如NeuroImage, Medical Image Analysis, Magnetic Resonance in Medicine, NMR in Biomed, Medical Physics, IEEE TCYB,IEEE TIM等共发表论文10余篇。在国际医学核磁共振学会年会ISMRM(磁共振领域最顶级国际学术会议,每年超7k人与会)发表会议论文 6篇(4 Oral Presentations) 。
2024年获得国际华人磁共振协会青年研究员奖(OCSMRM-YIA)。
2022年在ISMRM大会上关于端到端QSM方法的报告获得了 ISMRM Magna Cum Laude Merit Award的荣誉(澳大利亚地区2022年唯一)。
2024年至今担任业界顶级期刊NeuroImage(神经成像领域排名第一)关于QSM及EPT成像方法特刊编辑(https://www.sciencedirect.com/journal/neuroimage/about/call-for-papers#emerging-insights-for-magnetic-susceptibility-and-electrical-properties-mapping 欢迎来稿)。
主持国家自然科学基金青年项目1项,湖南省自然科学基金青年项目1项。参与国家自然科学基金国际合作项目等科研项目多项。
【硕士招生】
每年招收2名左右硕士研究生,欢迎对医学影像重建与处理、脑/神经成像、磁共振成像、人工智能、深度学习感兴趣的同学与我联系,课题组会为每一位学生提供良好的科研条件和生活补助。(邮箱:yang.gao@csu.edu.cn)。
课题组与国内外多家研究单位(如澳大利亚昆士兰大学、加拿大卡尔加里大学)有长期合作,可以为每位同学的发展提供尽可能多的支持。
主要期刊论文(完整列表见谷歌学术主页):
Yang Gao, et al., Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks, Medical Image Analysis (SCI, JCR 1, IF: 10.9). 2024, https://doi.org/10.1016/j.media.2024.103160.
Yang Gao, Martijn Cloos, Feng Liu, Stuart Crozier, G. Bruce Pike, Hongfu Sun. Accelerating Quantitative Susceptibility and R2* Mapping using Incoherent Undersampling and Deep Neural Network Reconstruction. NeuroImage, 2021, 240: 118404, (SCI, JCR 1, IF:6.556, Top1 in Neuroimaging).
Yang Gao, Zhuang Xiong, Amir Fazlollahi, Peter Nestor, Vector Vegh, Fatima Nasrallah, Craig Winter, G. Bruce Pike, Stuart Crozier, Feng Liu, Hongfu Sun. Instant magnetic tissue field and susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks. NeuroImage, 2022, (SCI, JCR 1, IF:6.556, Top1 in Neuroimaging).
Yang Gao,Xuanyu Zhu,Bradford A. Moffat,Rebecca Glarin,Alan H. Wilman,G. Bruce Pike,Stuart Crozier,Feng Liu,Hongfu Sun. xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks. NMR Biomed, 2021, 34(3): p. e4461, (SCI, JCR 1, IF 4.044).
Hongping Gan, Yang Gao*, Chunyi Liu, Haiwei Chen, Tao Zhang, Feng Liu. AutoBCS: Block-based Image Compressive Sensing with Data-driven Acquisition and Non-iterative Reconstruction. IEEE Transactions on Cybernetics, 2021, (SCI, JCR 1, IF:11.448) DOI: https://doi.org/10.1109/TCYB.2021.3127657. (通讯作者)
Shanshan, Shan, Yang Gao*, et al. Image Reconstruction with B0 Inhomogeneity using a Deep Unrolled Network on an Open-bore MRI-Linac, 2024, IEEE Transactions on Instrumentation and Measurement. (SCI, JCR, Q1, 通讯作者) . https://ieeexplore.ieee.org/document/10720147
Shanshan Shan#, Yang Gao#, Paul Z.Y. Liu, Brendan Whelan, Hongfu Sun, Feng Liu, David E.J. Waddington. Distortion-Corrected Image Reconstruction with Deep Learning on an MRI-Linac. Magnetic Resonance in Medicine, 2022. (SCI, JCR 1). (共同第一作者)
ISMRM会议论文列表:
Yang Gao, Zhuang Xiong, Stuart Crozier, Feng Liu, Hongfu Sun. QSM from the raw phase using an end-to-end neural network. International Society for Magnetic Resonance in Medicine 31th Scientific Meeting-ISMRM, online meeting. 2022. (Oral presentation, Magna Cum Laude Merit Award)
Yang Gao, Xuanyu Zhu, Stuart Crozier, Feng Liu, Hongfu Sun. xQSM: a deep learning QSM network using Octave Convolution. International Society for Magnetic Resonance in Medicine 29th Scientific Meeting-ISMRM, online meeting, 08-14 August 2020. (Oral presentation)
Yang Gao, Stuart Crozier, Feng Liu, G Bruce Pike, Hongfu Sun. Accelerating QSM using Compressed Sensing and Deep Neural Network. International Society for Magnetic Resonance in Medicine 30th Scientific Meeting-ISMRM, online meeting, 15-20 May, 2021. (Oral presentation)
Yang Gao, Tianyi Ding, Martjn Cloos, Hongfu Sun. MRF-mixer: a self-supervised deep learning MRF framework. International Society for Magnetic Resonance in Medicine 32th Scientific Meeting-ISMRM. 2023. (Oral presentation)
Yang Gao, et al., QSM Reconstruction of Arbitrary Dipole Orientations using an End-to-end Neural Network via Latent Feature Editing, 2024, ISMRM. Singapore, Digital Poster.
Chen Chen, Yang Gao*, et al., LoopNet: A New Baseline Network for QSM Dipole Inversion, 2024, ISMRM. Singapore, Digital Poster.
教育经历
[1] 2018.2-2022.7
昆士兰大学
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电子科学与技术
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博士学位
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博士研究生毕业
博士
工作经历
[1] 2022.11-至今
中南大学
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计算机学院
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全职
社会兼职
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[1] 业界顶级期刊NeuroImage特刊编辑
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[2] Session chair of the section "Biomedical Image Analysis" in APBC2023.
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[3] 多个国际顶级期刊如JMRI,MEDIA, MRM,NeuroImage,NMR in Biomed,IEEE JBHI 审稿人
其他联系方式
[6] 邮箱: