mlsanityData to 7 Oct 2026

Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20× Speedup

arXiv 2209.15136 ↗First posted 29 Sep 2022eess.IV cs.LG eess.SPcited by 3

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Low-dose computed tomography (LDCT) is an important topic in the field of radiology over the past decades. LDCT reduces ionizing radiation-induced patient health risks but it also results in a low signal-to-noise ratio (SNR) and a potential compromise in the diagnostic performance. In this paper, to improve the LDCT denoising performance, we introduce the conditional denoising diffusion probabilistic model (DDPM) and show encouraging results with a high computational efficiency. Specifically, given the high sampling cost of the original DDPM model, we adapt the fast ordinary differential equation (ODE) solver for a much-improved sampling efficiency. The experiments show that the accelerated DDPM can achieve 20x speedup without compromising image quality.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 29 of its 52 references that are in the map. First posted on arXiv 29 Sep 2022.

Builds on

29 of 52 references.

References · 29

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17 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 1; 2026: 1.

3 papers.

  1. 2025D-PerceptCT: Deep Perceptual Enhancement for Low-Dose CT Imagescited by 1
  2. 2023Diffusion Denoising for Low-Dose-CT Modelcited by 0
  3. 2026GenDiff: A Dose and Anatomy Aware Diffusion Model with Structural Prior Refinement for Low-Dose CT Reconstruction and Generalizationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstruction
  2. 2026TAFG-MAN: Timestep-Adaptive Frequency-Gated Latent Diffusion for Efficient and High-Quality Low-Dose CT Image Denoising
  3. 2026ProSAC-CT: Progressive Spectral-Anatomical Co-Guided Multi-Stage Diffusion Model for Low-Dose CT Denoising
  4. 2023Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT
  5. 2025AST-n: A Fast Sampling Approach for Low-Dose CT Reconstruction using Diffusion Models
  6. 2026RDDM: A Residual-Driven Drifting Model for High-Fidelity Low-Dose CT Denoising
  7. 2023CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization
  8. 2025FD-DiT: Frequency Domain-Directed Diffusion Transformer for Low-Dose CT Reconstruction