mlsanityData to 14 Oct 2026

Towards Diagnostic Quality Flat-Panel Detector CT Imaging Using Diffusion Models

arXiv 2508.16252 ↗First posted 22 Aug 2025eess.IV cs.CVcited by 0

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Abstract (arXiv)

Patients undergoing a mechanical thrombectomy procedure usually have a multi-detector CT (MDCT) scan before and after the intervention. The image quality of the flat panel detector CT (FDCT) present in the intervention room is generally much lower than that of a MDCT due to significant artifacts. However, using only FDCT images could improve patient management as the patient would not need to be moved to the MDCT room. Several studies have evaluated the potential use of FDCT imaging alone and the time that could be saved by acquiring the images before and/or after the intervention only with the FDCT. This study proposes using a denoising diffusion probabilistic model (DDPM) to improve the image quality of FDCT scans, making them comparable to MDCT scans. Clinicans evaluated FDCT, MDCT, and our model's predictions for diagnostic purposes using a questionnaire. The DDPM eliminated most artifacts and improved anatomical visibility without reducing bleeding detection, provided that the input FDCT image quality is not too low. Our code can be found on github.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 34 references that are in the map. First posted on arXiv 22 Aug 2025.

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11 of 34 references.

References · 11

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  3. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  4. 2021Palette: Image-to-Image Diffusion Modelscited by 1,300
  5. 2021Diffusion Models for Implicit Image Segmentation Ensemblescited by 198
  6. 2022SynthStrip: Skull-Stripping for Any Brain Imagecited by 127
  7. 2023Generative AI for Medical Imaging: extending the MONAI Frameworkcited by 68
  8. 2023SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapycited by 53
  9. 2023Diffusion Models for Contrast Harmonization of Magnetic Resonance Imagescited by 19
  10. 2024cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image Synthesiscited by 19
  11. 2024Deep Generative Models for 3D Medical Image Synthesiscited by 14

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  5. 2022Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction
  6. 2023Diffusion Denoising for Low-Dose-CT Model
  7. 2026Cone-Beam CT Image Quality Enhancement Using A Latent Diffusion Model Trained with Simulated CBCT Artifacts
  8. 2026DM4CT: Benchmarking Diffusion Models for Computed Tomography Reconstruction