[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.
