Preprints, Publications

  Google scholar   Github repositories

Preprints

  1. Personalized Artifacts Modeling and Federated Learning for Multi-institutional Low Dose CT Reconstruction
    J. Xu, Q. Ding, Y. Zhu, X. Zhang  
  2. Dual-Domain Deep D-bar Method for Solving Electrical Impedance Tomography
    X. Cao, Q. Ding, X. Zhang  
  3. A fully automated U-net based ROIs localization and bone age assessment method
    Y. Zhao, Y. Wang, H.Yuan, W. Xie, Q. Ding, X. Zhang  
  4. Statistical image reconstruction using mixed Poisson-Gaussian noise model for X-ray CT
    Q. Ding, Y. Long, X. Zhang, J. A. Fessler (Arxiv)

Journal papers

  1. Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport
    Z. Xiong, Q. Ding, X. Zhang, SIAM Imaging. Accepted.
  2. Automatic recognition of white blood cell images with memory efficient superpixel metric GNN: SMGNN
      Y. Jiang, Y. Shen, Y. Wang, Q. Ding，Mathematical Biosciences and Engineering, 2024 Jan 10;21(2):2163-2188. doi: 10.3934/mbe.2024095.
  3. Vision Graph U-Net: Geometric Learning Enhanced Encoder for Medical Image Segmentation and Restoration
      Y. Jiang, Q. Ding, Y. Wang, P. Lio, X. Zhang，Inverse Problems and Imaging, 2024. Doi: 10.3934/ipi.2023049
  4. SEA-Net: Structure-Enhanced Attention Network for Limited-Angle CBCT Reconstruction of Clinical Projection Data
      D. Hu, Y. Zhang, W. Li, W. Zhang, K. Reddy, Q. Ding, X. Zhang, Y. Chen, H. Gao，IEEE Transactions on Instrumentation & Measurement, 2023.
  5. A shortened model for Logan reference plot implemented via the self-supervised neural network for parametric imaging with dynamic PET
      W. Ding, Q. Ding, K. Chen, M. Zhang, L. Lv, D. Feng, J. Kim, L. Bi, H. Qiu, IEEE Transactions on Medical Imaging (TMI), vol. 42, no. 10，2023.
  6. The Prognostic Value of Splenic Abnormalities in Pretreatment 18F- FDG PET/CT in patients with Complete Response Diffuse Large B-cell Lymphoma
      S. Wang, H. Ju, Y. Bai, L. Wang, Q. Ding, X. Jiang, P. Li, X. Lin, Clinical Oncology, 2023.
  7. A Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction
      Q. Ding, H. Ji, Y. Quan and X. Zhang, Inverse Problems 38(10): 104003, 2022.
  8. Nomogram based on Clinical and Radiomics Data for Predicting Radiation-induced Temporal Lobe Injury in Patients with Non-metastatic Stage T4 Nasopharyngeal Carcinoma
      X. Bin, C. Zhu, Y. Tang, R. Li, Q, Ding, Clinical Oncology 34(12) e482-e492, issn 0936-6555, 2022.
  9. Deep Learning With Adaptive Hyper-Parameters for Low-Dose CT Image Reconstruction
      Q. Ding, Y. Nan, H. Gao and H. Ji, IEEE Transactions on Computational Imaging (TCI), vol. 7, pp. 648-660, doi: 10.1109/TCI.2021.3093003. 2021.
  10. AirNet: Fused analytical and iterative reconstruction with deep neural network regularization for sparse-data CT
      G. Chen, X. Hong Q. Ding and so on. Medical Physics, 2020.
  11. Low-dose CT with deep learning regularization via proximal forward backward splitting
     Q. Ding, G. Chen, X. Zhang, Q. Huang, H. Ji and H. Gao, Physics in Medicine and Biology, 2020.
  12. Image-domain multimaterial decomposition for dual-energy CT based on prior information of material images
      Q. Ding, T. Niu, X. Zhang and Y. Long, Medical physics, 45(8): 3614-3626, 2018.
  13. Dynamic SPECT reconstruction with temporal edge correlation
      Q. Ding, M. Burger and X. Zhang, Inverse Problems, 34(1): 014005, 2017.
  14. Dynamic SPECT reconstruction from few projections: a sparsity enforced matrix factorization approach
      Q. Ding, Y. Zan, Q. Huang and X. Zhang, Inverse Problems, 31(2)： 025004, 2015. (Insight Paper)

Conference proceedings

  1. SyMOT-Flow: Learning optimal transport flow for two arbitrary distributions with maximum mean discrepancy
      Z. Xiong, Q. Ding, X. Zhang , NeurIPS Optimal Transport and Machine Learning Workshop, 2023.
  2. PET-3DFlow: A Normalizing Flow Based Method for 3D PET Anomaly Detection
      Z. Xiong, Q. Ding, Y. Zhao, X. Zhang , MICCAI Workshop, 2023.
  3. AE-FLOW: Autoencoders with Normalizing Flows for Medical Images Anomaly Detection
      Y. Zhao, Q. Ding, X. Zhang , ICLR, 2023.
  4. MRI Reconstruction by Completing Under-sampled K-space Data with Learnable Fourier Interpolation
      Q. Ding and X. Zhang, MICCAI, 2022.
  5. Learnable multi-scale fourier interpolation for sparse view CT image reconstruction
      Q. Ding, H. Ji, H. Gao and X. Zhang, MICCAI, 2021. (Top 13% Papers)
  6. Image-domain multi-material decomposition for dual-energy CT via total nuclear norm and l0 norm
      Q. Ding, T. Niu, X. Zhang and Y. Long, Fully3D, 2017. (Oral, Student Travel Award)
  7. Modeling mixed Poisson-Gaussian noise in statistical image reconstruction for X-ray CT
      Q. Ding, Y. Long, X. Zhang and J. A. Fessler, Proc. 4th Intl. Mtg. on Image Formation in X-ray CT (CT meeting), 2016. (Oral)

Poster

  1. Deep Learning with Adaptive Hyper-Parameters for Image Reconstruction in Low-Dose CT
      Q. Ding, Y. Nan H. Ji and H. Gao, AAPM ePoster, BReP-SNAP-I-14, 2020.
  2. Low-Dose CT with Deep Learning Regularization Via PFBS
      Q. Ding, H.Ji and H. Gao, AAPM ePoster, BReP-SNAP-I-60, 2019.

PhD Thesis