夏文军，博士，现任东南大学计算机科学与工程学院教师。2012年和2022年分别于四川大学获得学士和博士学位，主要从事CT成像理论与人工智能重建方法研究。博士后期间在美国伦斯勒理工学院（Rensselaer Polytechnic Institute）生物医学工程系开展研究工作，与IEEE Life Fellow、AAPM和SPIE Fellow、IEEE TMI主编Ge Wang教授合作，探索生成式人工智能与CT重建的融合机制。在IEEE TMI、IEEE SPM、MICCAI等国际顶级期刊与会议发表论文30余篇篇。长期担任IEEE TMI、MICCAI、Medical Physics等期刊审稿人。 |
2008-09 至 2012-06 四川大学 本科学士
2017-09 至 2022-06 四川大学 软件工程 博士
2022-08 至 2025-08, 伦斯勒理工学院, 博士后
2025-10 至今， 东南大学计算机科学与工程学院， 副教授
[1] Xia W, Yang Z, Lu Z, Wang Z, Zhang Y, “RegFormer: A Local-Nonlocal Regularization-Based Model for Sparse-View CT Reconstruction,” IEEE Transactions on Radiation and Plasma Medical Sciences, pp. 1–1, 2023.
[2] Xia W, Shan H, Wang G, Zhang Y, “Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey,” IEEE Signal Processing Magazine, vol. 40, no. 2, pp. 89–100, Mar. 2023.
[3] Xia W, Yang Z, Zhou Q, Lu Z, Wang Z, Zhang Y, “A Transformer-Based Iterative Reconstruction Model for Sparse-View CT Reconstruction,” in Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, L. Wang, Q. Dou, P. T. Fletcher, S. Speidel, and S. Li, Eds., in Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2022, pp. 790–800.
[4] Xia W, Lu Z, Huang Y, Shi Z, Liu Y, Chen H, Chen Y, Zhou J, Zhang Y, “MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction,” IEEE Transactions on Medical Imaging, vol. 40, no. 12, pp. 3459–3472, Dec. 2021.
[5] Xia W, Lu Z, Huang Y, Liu Y, Chen H, Zhou J, Zhang Y, “CT Reconstruction With PDF: Parameter-Dependent Framework for Data From Multiple Geometries and Dose Levels,” IEEE Transactions on Medical Imaging, vol. 40, no. 11, pp. 3065–3076, Nov. 2021.
[6] Xia W, Wu W, Niu S, Liu F, Zhou J, Yu H, Wang G, Zhang Y, “Spectral CT Reconstruction—ASSIST: Aided by Self-Similarity in Image-Spectral Tensors,” IEEE Transactions on Computational Imaging, vol. 5, no. 3, pp. 420–436, Sep. 2019.
[7] Lee W, Wagner F, Galdran A, Shi Y, Xia W, Wang G, Mou X, Ahamed MA, Imran AA, Oh JE, Kim K, Low-dose computed tomography perceptual image quality assessment. Medical Image Analysis, vol. 99, p.103343, Jan. 2025.
[8] Zhang Q, Alvandipour M, Xia W, Zhang Y, Ye X, Chen Y, Provably convergent learned inexact descent algorithm for low-dose ct reconstruction. Journal of Scientific Computing, vol. 101, no. 1, p. 10, Oct. 2024.
[9] Karageorgos GM, Zhang J, Peters N, Xia W, Niu C, Paganetti H, Wang G, De Man B. A denoising diffusion probabilistic model for metal artifact reduction in CT. IEEE Transactions on Medical Imaging. Jul. 4, 2024.
[10] Shi Y, Xia W, Wang G, Mou X. Blind ct image quality assessment using ddpm-derived content and transformer-based evaluator. IEEE Transactions on Medical Imaging. Jun. 24, 2024.
[11] Xia W, Tseng HW, Niu C, Cong W, Zhang X, Liu S, Ning R, Vedantham S, Wang G, “Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT.” arXiv:2303.12861, Jan. 28, 2024.
[12] Wang Z, Li B, Yu H, Zhang Z, Ran M, Xia W, Yang Z, Lu J, Chen H, Zhou J, “Promoting fast MR imaging pipeline by full-stack AI,” iScience, vol. 27, no. 1, p. 108608, Jan. 2024.
[13] Cong W, Xia W, Wang G, “Image Reconstruction Using a Mixture Score Function (MSF).” arXiv, Jan. 09, 2024.
[14] Zhang Y, Chen H, Xia W, Chen Y, Liu B, Liu Y, Sun H, Zhou J, “LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CT,” IEEE Trans. Radiat. Plasma Med. Sci., vol. 7, no. 2, pp. 132–142, Feb. 2023.
[15] Yang Z, Xia W, Qiao Y, Lu Z, Zhang B, Leng L, Zhang Y, “CO3Net: Coordinate-Aware Contrastive Competitive Neural Network for Palmprint Recognition,” IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1–14, 2023.
[16] Yang Z, Xia W, Lu Z, Chen Y, Li X, Zhang Y, “Hypernetwork-Based Physics-Driven Personalized Federated Learning for CT Imaging,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1–15, 2023.
[17] Xia W, Shi Y, Niu C, Cong W, Wang G, “Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT.” arXiv, Oct. 10, 2023.
[18] Wang T, Xia W, Lu J, Zhang Y, “A Review of Deep Learning CT Reconstruction from Incomplete Projection Data,” IEEE Transactions on Radiation and Plasma Medical Sciences, pp. 1–1, 2023.
[19] Wang H, Wang G, Xia W, Yang Z, Yu H, Fang L, Zhang Y, “Blind Image Quality Assessment via Deep Response Feature Decomposition and Aggregation,” IEEE Journal of Selected Topics in Signal Processing, vol. 17, no. 6, pp. 1165–1177, Nov. 2023.
[20] Shen C, Xia W, Ye H, Hou M, Chen H, Liu Y, Zhou J, “Unsupervised Bayesian PET Reconstruction,” IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 7, no. 2, pp. 175–190, Feb. 2023.
[21] Lu Z, Xia W, Huang Y, Hou M, Chen H, Zhou J, Shan H, Zhang Y, “M3NAS: Multi-Scale and Multi-Level Memory-Efficient Neural Architecture Search for Low-Dose CT Denoising,” IEEE Transactions on Medical Imaging, vol. 42, no. 3, pp. 850–863, Mar. 2023.
[1] 张意; 夏文军; 周激流 ; 基于空谱双域张量自相似的能谱CT重建方法, 2020-08-04, 中国, CN201910160075.9
[2] 杨康; 张意; 夏文军; 包鹏; 周激流 ; 基于加权核范数极小的稀疏角CT图像重建方法, 2021-05-14,中国, CN201811482556.3
[1] 2023 AAPM 医学图像统计深度生成建模挑战赛（DGM-Image）第一名, 伊利诺伊大学厄巴纳–香槟分校、圣路易斯华盛顿大学、美国食品药品监督管理局（FDA）、Puente Solutions有限责任公司联合主办
[2] 2023 MICCAI 低剂量CT感知图像质量评估挑战赛(LDCTIQA 2023)第二名, 韩国梨花女子大学、韩国延世大学、德国埃尔朗根–纽伦堡大学、美国斯坦福大学和美国梅奥诊所联合主办
