ArticleProceedings of SPIE--the International Society for Optical Engineering2024
Diffusion Posterior Sampling for Nonlinear CT Reconstruction.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- A comparative study of diffusion-based reconstruction frameworks for photoacoustic tomography.Scientific reports · 2026Article
- CT Radiation Dose Reduction With Preserved Diagnostic Performance: How Far Have We Come Over 25 Years?AJR. American journal of roentgenology · 2026Review
- Diffusion Posterior Sampling for Tomographic Reconstruction with Mixed Resolution Priors.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Evaluation of Fluence Reduction versus Sparsity for Diffusion Posterior Sampling Reconstruction in Low-Dose CT.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Multi-Material Decomposition Using Spectral Diffusion Posterior Sampling.IEEE transactions on bio-medical engineering · 2025Article
- Joint Reconstruction and Scatter Estimation in Cone-beam CT using Diffusion Posterior Sampling.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- 3D Diffusion Posterior Sampling for CT Reconstruction.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- CT reconstruction using diffusion posterior sampling conditioned on a nonlinear measurement model.Journal of medical imaging (Bellingham, Wash.) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Diffusion models have been demonstrated as powerful deep learning tools for image generation in CT reconstruction and restoration. Recently, diffusion posterior sampling, where a score-based diffusion prior is combined with a likelihood model, has been used to produce high quality CT images given low-quality measurements. This technique is attractive since it permits a one-time, unsupervised training of a CT prior; which can then be incorporated with an arbitrary data model. However, current methods only rely on a
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.