伍伟文
个人基本信息 (Personal Information)
姓名 (Name):伍伟文 (Weiwen Wu)
职称 (Title):副教授/硕士生导师 (Associate Professor)
电子邮箱 (E-mail): wuweiw7@mail.sysu.edu.cn
办公室 (Office):中山大学深圳校区医学园2栋604B室
个人主页:https://scholar.google.com/citations?user=T4o77REAAAAJ&hl=en&oi=ao
工作经历 (Working Experience)
2021.12-至今:中山大学,生物医学工程学院,“百人计划”副教授
2020.12-2021.12:美国伦斯勒理工学院,生物医学工程学院,博士后
2019.08-2020.12:香港大学,李嘉诚医学院,博士后
教育经历 (Education)
2014.09-2019.06:重庆大学,仪器科学与技术,工学博士
2017.09-2018.10:马萨诸塞州立大学洛厄尔分校,联合博士
2010.09-2014.06:南昌航空大学,测控技术与仪器,工学学士
研究方向 (Research Interest)
1. 智能能谱CT成像技术:基于光子计数探测器的能谱CT被认为是下一代新型CT技术,在降低病人辐射剂量、减小金属伪影、提高空间分辨力和软组织对比度等方面具有巨大的前景。然而,能谱CT测量数据具有噪声大,本项目聚焦于对能谱成像方式的深度理解,发展基于智能化的能谱CT重建技术。
2. 深度学习欠采样数据恢复:如何从欠采样的数据中恢复出高质量的图像总是成像技术中面临的一大挑战,包括核磁共振成像和CT成像等。本项目的目标聚焦于少量极端数据情况恢复出高质量的重建图像。典型应用就是CT成像中有限角度重建,稀疏角度重建等。
3. 实时CT成像系统设计:实时成像一直是CT成像追求的目标,有利于解决对包括心脏成像等在内的动态成像场合。该项目通过设计新型CT实时成像系统,发展基于人工智能的快速成像可靠的重建算法。
4. 低剂量CT成像:低造影剂剂量和低辐射剂量是CT成像的主要追求目标,本项目一方面聚焦实现低辐射剂量下高质量成像,另一方面同样也着重关注在低对比剂剂量增强成像,通过发展基于深度学习成像模型,最终实现双低剂量CT成像。
科研项目(Funding Projects)
从2022年开始,所主持的项目一直是围绕从X射线成像和系统开发方向,获批的项目包括国家自然基金面上/青年项目、国家重点研发计划子课题和广东省自然科学基金面上项目等。
论著成果 (Selected Publications)
目前作为累计发表SCI论文30余篇,其中第一作者/通信作者包括IEEE Transactions on Image Processing、IEEE Transactions on Medical Imaging、Medical Image Analysis、Inverse Problems、Neural Networks等SCI期刊发表论文30余篇。部分代表性期刊论文(*为通讯作者):
[1] Jiayi Pan, Hengyong Yu, Zhifan Gao, Shaoyu Wang, Heye Zhang, Weiwen Wu*. “Iterative Residual Optimization Network for Limited-angle Tomographic Reconstruction [J]”. IEEE Transactions on Image Processing, vol. 33, pp. 910-925, 2024.
[2] Weiwen Wu, Dianlin Hu, Chuang Niu, Hengyong Yu*, Varut Vardhanabhuti*, Ge Wang*. “DRONE: Dual-domain Residual-based Optimization NEtwork for Sparse-view CT Reconstruction [J]”. IEEE Transactions on Medical Imaging, 40: 3002-3014, 2021.
[3] Weiwen Wu, Yanyang Wang, Qiegen Liu, Ge Wang*, Jianjia Zhang*. “Wavelet-improved Score-based Generative Model for Medical Imaging[J]”. IEEE Transactions on Medical Imaging, vol. 43, no. 3, pp. 966-979, 2024.
[4] Kai Xu, Shiyu Lu, Bin Huang, Weiwen Wu*, Qiegen Liu*. “Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-View CT Reconstruction [J]”. IEEE Transactions on Medical Imaging, 2024, doi: 10.1109/TMI.2024.3355455.
[5] Jianjia Zhang, Yunan Guo, Luping Zhou, Lei Wang, Weiwen Wu*, Dinggang Shen*. “Constructing Hierarchical Attentive Functional Brain Networks for Early AD Diagnosis [J]”. Medical Image Analysis, 2024, doi: 10.1016/j.media.2024.103137.
[6] Jianjia Zhang, Haiyang Mao, Xinran Wang, Yuan Guo, Weiwen Wu*. “Wavelet-Inspired Multi-channel Score-based Model for Limited-angle CT Reconstruction [J]”. IEEE Transactions on Medical Imaging, 2024, doi: 10.1109/TMI.2024.3367167.
[7] Weiwen Wu*, Jiayi Pan, Yanyang Wang, Shaoyu Wang*, Jianjia Zhang*. “Multi-channel Optimization Generative Model for Stable Ultra-Sparse-View CT Reconstruction [J]”. IEEE Transactions on Medical Imaging, 2024, doi: 10.1109/TMI.2024.3376414.
[8] Weiwen Wu, Fenglin Liu*, Yanbo Zhang, Qian Wang, Hengyong Yu*. “Non-local low-rank cube-based tensor factorization for spectral CT reconstruction [J]”. IEEE Transactions on Medical Imaging, 38: 1079-1093, 2019.
[9] Jianjia Zhang, Zhenxi Zhang, Lei Wang, Luping Zhou, Xiaocai Zhang, Mengting Liu*, Weiwen Wu*. “Kernel-based feature aggregation framework in point cloud networks [J]”. Pattern Recognition, 139: 109439, 2023.
[10] Weiwen Wu, Dianlin Hu, Chuang Niu, Lieza Vanden Broeke, Anthony P.H. Butler, Peng Cao, James Atlas, Alexander Chernoglazov, Varut Vardhanabhuti*, Ge Wang. “Deep learning based spectral CT Imaging [J]”. Neural Networks, 144, 342-358, 2021.
[11] Xiaodong Guo, Yonghui Li, Dingyue Chang, Peng He, Peng Feng*, Hengyong Yu*, Weiwen Wu*. “Spectral2Spectral: Image-Spectral Similarity Assisted Deep Spectral CT Reconstruction Without Reference [J]”. IEEE Transactions on Computational Imaging, vol. 9, pp. 1031-1042, 2023.
[12] Weiwei Zhang, Zhen Zhou, Zhifan Gao, Guang Yang, Lei Xu, Weiwen Wu*, Heye Zhang*. “Multiple Adversarial Learning based Angiography Reconstruction for Ultra-low-dose Contrast Medium CT [J]”. IEEE Journal of Biomedical and Health Informatics, 27(1): 409-421, 2023.(ESI高被引)
[13] Yanyang Wang, Zirong Li, Weifei Wu, Jianjia Zhang*, Weiwen Wu*. “Self-fusion Simplex Noise-based Diffusion Model for Self-supervised Low-dose Digital Radiography Denoising [J]”. IEEE Transactions on Instrumentation and Measurement, 2024, doi: 10.1109/TIM.2024.3375967.
[14] Zirong Li, Kang An, Hengyong Yu, Fulin Luo, Jiayi Pan, Shaoyu Wang, Jianjia Zhang, Weiwen Wu*, Dingyue Chang*. “Spectrum Learning for Super-resolution Tomographic Reconstruction [J]”. Physics in Medicine & Biology, 2024, doi: 10.1088/1361-6560/ad2a94.
[15] Zirong Li, Yanyang Wang, Jianjia Zhang, Weiwen Wu*, Hengyong Yu*. “Two-and-a-half order score-based model for solving 3D ill-posed inverse problems [J]”. Computers in Biology and Medicine, 168: 107819, 2024.
[16] Weiwen Wu, Yanbo Zhang, Qian Wang, Fenglin Liu*, Fulin Luo, and Hengyong Yu*. “Spatial-Spectral Cube Matching Frame for Spectral CT Reconstruction [J]”. Inverse Problems, 34: 104003, 2018.
招聘与招生 (Join Us)
博士后招聘
长期招聘多名医学图像处理方向的博士后,申请者需具有(或即将拿到)计算机、电子信息、控制、数学、生物医学工程等相关专业背景的博士学位。
硕士研究生招生/实习
欢迎有志于科学研究的保研/考研的同学联系我。我们将一起在人工智能、医学成像、硬件系统设计方面等挖掘新的科学问题和应用点,进行新的探索和尝试。同时欢迎在读硕士来实验室实习(本校外校均可)。适合对我的研究方向感兴趣、并准备今后攻读博士学位或出国深造的同学,本课题组与香港大学、伦斯勒理工学院以及马萨诸塞州立大学洛厄尔分校等有深入合作交流的机会。期待计算机、电子信息、控制、数学、生物医学工程等相关专业背景的同学联系我。
长期招收本科生实习
欢迎本科同学和我一起进行科学研究,对本科同学的指导是以兴趣+学术为导向,主要培养科研兴趣、学术思维和探索能力,并且支持和鼓励本科同学将研究成果发表在学术论文上,或是以参加学术报告的方式对外展示。表现优异者可支持出国参加高水平的学术会议。适合对科研有浓厚兴趣的,或有志于在中山大学继续深造、申请出国攻读硕士/博士学位的同学。期待本科1-3年级,具有一定大学数学和编程基础的同学联系我;也欢迎外校的同学来实验室进行交流。