赵维 - 北京航空航天大学

个人简介

赵维，男，博士，北京航空航天大学物理学院教授、博士生导师。本科和博士分别毕业于兰州大学和中国科学院高能物理研究所。先后在美国威斯康星大学麦迪逊分校，华中科技大学和斯坦福大学从事研究和开发工作。研究方向为医学物理，具体从事CT成像及其在图像引导放射治疗中的机理和应用研究。荣获美国放射肿瘤学会基础转化科学奖和国际光学工程学会医学影像青年科学家奖。发表学术论文62篇，其中以第一/通讯作者在顶级期刊Nature Biomedical Engineering，International Journal of Radiation Oncology • Biology • Physics(红皮书)，Radiotherapy and Oncology（绿皮书）和医学物理领域权威期刊Medical Physics，Physics in Medicine and Biology，IEEE Transactions on Computational Imaging等发表论文30篇。获授权、公开和申请中美等发明专利超过10件。在本领域国际大会作口头报告和邀请报告20余次，撰写中英文图书章节4章。主持国家自然科学基金、浙江省自然科学基金重点项目等。研究内容瞄准医学物理核心问题和临床及工业应用需求，研究成果具有产业转化的价值，已成功转化至国内外公司。教育经历 2007.9 -- 2012.7 中国科学院高能物理研究所博士研究生博士学位 2003.9 -- 2007.7 兰州大学物理学本科学士学位工作经历 2021.1 -- 至今北京航空航天大学教授 2016.10 -- 2020.12 斯坦福大学研究科学家 2012.10 -- 2014.9 美国威斯康星大学麦迪逊分校博士后社会兼职科学出版社“十四五”普通高等教育研究生规划教材编委中国核学会医学物理分会理事北京核学会理事中国生物医学工程学会医学物理青年委员会秘书长医学图像计算青年研讨会（MICS）委员中国生物医学工程学会精确放疗技术分会委员中国体视学学会青年工作委员会委员《核电子学与核探测技术》编委任国际原子能机构人类健康部门评审员

研究领域

医学物理人工智能图像引导放疗 CT成像医学物理核技术及应用

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Fast Scatter Artifacts Correction for Cone-Beam CT without System Modification and Repeat Scan MO-FG-204-03: Using Edge-Preserving Algorithm for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT Iterative CT shading correction with no prior information Energy Spectrum Extraction and Optimal Imaging via Dual-Energy Material Decomposition A Model-Based Scatter Artifacts Correction for Cone Beam CT A qualitative study of improving megavoltage computed tomography image quality and maintaining dose accuracy using cycleGAN-based image synthesis Commissioning dose computation model for proton source in pencil beam scanning therapy by convolution neural networks Application of PET-LINAC in Biology-guided Radiotherapy Improving anisotropy resolution of computed tomography and annotation using 3D super-resolution network Less Is More: Surgical Phase Recognition From Timestamp Supervision Modeling linear accelerator (Linac) beam data by implicit neural representation learning for commissioning and quality assurance applications SWFT-Net: a deep learning framework for efficient fine-tuning spot weights towards adaptive proton therapy Leveraging data-driven self-consistency for high-fidelity gene expression recovery AI-Augmented Images for X-Ray Guiding Radiation Therapy Delivery Editorial: Machine learning in radiation oncology Review of Radiomics- and Dosiomics-based Predicting Models for Rectal Cancer Mitigating the uncertainty in small field dosimetry by leveraging machine learning strategies Virtual computed-tomography system for deep-learning-based material decomposition A geometry-informed deep learning framework for ultra-sparse 3D tomographic image reconstruction PD-0324 A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction A generalized image quality improvement strategy of cone-beam CT using multiple spectral CT labels in Pix2pix GAN Dose prediction via distance-guided deep learning: Initial development for nasopharyngeal carcinoma radiotherapy Less is More: Surgical Phase Recognition from Timestamp Supervision Novel-view X-ray Projection Synthesis through Geometry-integrated Deep Learning SERM: a self-consistent deep learning solution for rapid and accurate gene expression recovery Artificial intelligence in image-guided radiotherapy: A review of treatment target localization Human-level comparable control volume mapping with a deep unsupervised-learning model for image guided radiation therapy Dose Prediction Using a Three-Dimensional Convolutional Neural Network for Nasopharyngeal Carcinoma With Tomotherapy Novel-View X-Ray Projection Synthesis Through Geometry-Integrated Deep Learning Enabling Few-View 3D Tomographic Image Reconstruction by Geometry-Informed Deep Learning Human-Level Comparable Control Volumes Mapping With an Unsupervised-Learning Model for CT-Guided Radiotherapy Automated Contour Propagation of the Prostate From pCT to CBCT Images via Deep Unsupervised Learning Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning Metal artifact reduction in 2D CT images with self-supervised cross-domain learning Noise2Context: Context-assisted Learning 3D Thin-layer for Low Dose CT High-resolution multicontrast tomography with an X-ray microarray anode–structured target source A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction Rotation-Oriented Collaborative Self-Supervised Learning for Retinal Disease Diagnosis CD-Net: Comprehensive Domain Network With Spectral Complementary for DECT Sparse-View Reconstruction TransCT: Transformer based Low Dose Computed Tomography Modularized Data‐Driven Reconstruction Framework for Non‐ideal Focal Spot Effect Elimination in Computed Tomography Automated Contour Propagation of the Prostate From pCT to CBCT Images Via Deep Unsupervised Learning Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network Noise2Context: Context-assisted Learning 3D Thin-layer Low Dose CT Without Clean Data Fiducial-Free Image-Guided Spinal Stereotactic Radiosurgery Enabled Via Deep Learning Mitigating the Uncertainty in Small Field Dosimetry for Stereotactic Body Radiation Therapy by Leveraging Machine Learning Strategies Enabling Novel View Synthesis for X-ray Projection Generation by Deep Learning Dual-energy CT Imaging Using a Single-energy CT Data via Deep Learning: A Contrast-enhanced CT Study Dual-energy Computed Tomography Imaging from Contrast-enhanced Single-energy Computed Tomography Beam data modeling of linear accelerators (linacs) through machine learning and its potential applications in fast and robust linac commissioning and quality assurance Beam data modeling of linear accelerators (linacs) through machine learning and its potential applications in fast and robust linac commissioning and quality assurance Whole-body tracking of single cells via positron emission tomography A Deep Learning Framework for Prostate Localization in Cone Beam CT Guided Radiotherapy Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network High‐speed X‐ray‐induced luminescence computed tomography A deep learning approach for virtual monochromatic spectral CT imaging with a standard single energy CT scanner Restarted primal-dual Newton conjugate gradient method for enhanced spatial resolution of reconstructed cone-beam X-ray luminescence computed tomography images Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning T1 measurement of bound water in cortical bone using 3D adiabatic inversion recovery ultrashort echo time (3D IR‐UTE) Cones imaging Flash放疗 Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning X-ray-induced shortwave infrared luminescence computed tomography Reduced acquisition time for L‐shell x‐ray fluorescence Computed tomography using polycapillary x‐ray optics Deep Learning Approach for Markerless Pancreatic Tumor Target Localization Radiation Activatable Radiosensitizers for Image-Guided and Enhanced Radiation Therapy against Head and Neck Cancer Harnessing the Power of Machine Learning for Accurate and Efficient Linear Accelerator Beam Data Commissioning CellGPS: Whole-body tracking of single cells by positron emission tomography Incorporating imaging information from deep neural network layers into image guided radiation therapy (IGRT) Automatic target positioning and tracking for image-guided radiotherapy without implanted fiducials Dual-energy CT imaging using a single-energy CT data is feasible via deep learning Markerless Pancreatic Tumor Target Localization Enabled By Deep Learning Scatter correction for a clinical cone‐beam CT system using an optimized stationary beam blocker in a single scan Fast quantitative 3D ultrashort echo time MRI of cortical bone using extended cones sampling Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI Fat suppression for ultrashort echo time imaging using a single‐point Dixon method Multi-materials beam hardening artifacts correction for computed tomography (CT) based on X-ray spectrum estimation Robust beam hardening artifacts reduction for computed tomography (CT) using spectrum modeling Whole knee joint T 1 values measured in vivo at 3T by combined 3D ultrashort echo time cones actual flip angle and variable flip angle methods Visualizing the Invisible in Prostate Radiation Therapy: Markerless Prostate Target Localization Via a Deep Learning Model and Monoscopic Kv Projection X-Ray Image Dual Modality Shortwave Infrared Fluorescence and Photoacoutic Imaging of Radiation-Induced Vascular Damage in Stereotactic Ablative Radiation Therapy Polarized X-ray excitation for scatter reduction in X-ray fluorescence computed tomography Synergistically Enhancing Therapeutic Effect of Radiation Therapy with Radiation Activatable and Reactive Oxygen Species-Releasing Nanostructures Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation A unified image reconstruction framework for quantitative dual- and triple-energy CT imaging of material compositions Synthesis, Characterization and Biomedical Applications of a Targeted Dual-Modal Near Infrared-II Fluorescence and Photoacoustic Imaging Nanoprobe Material Decomposition Using Triple-Energy CT for Accurate Proton Therapy Dose Calculation Segmentation-Free X-ray Energy Spectrum Estimation for Computed Tomography Using Dual-Energy Material Decomposition SU-F-I-41: Calibration-Free Material Decomposition for Dual-Energy CT Absorption imaging performance in a future Talbot-Lau interferometer based breast imaging system Patient-specific scatter correction for flat-panel detector-based cone-beam CT imaging An indirect transmission measurement-based spectrum estimation method for computed tomography