Evidence map›Paper›PMID 42017038›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2026

Evaluation of Fluence Reduction versus Sparsity for Diffusion Posterior Sampling Reconstruction in Low-Dose CT.

Zimo Liu, Xin Wang, Xiao Jiang, Altea Lorenzon, Grace J Gang, J Webster Stayman

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In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zimo LiuDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore MD, 21205, USA.
Xin WangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore MD, 21205, USA.
Xiao JiangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore MD, 21205, USA.
Altea LorenzonDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore MD, 21205, USA.
Grace J GangDepartment of Radiology, University of Pennsylvania, Philadelpha PA, 19104, USA.
J Webster StaymanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore MD, 21205, USA.

Funding

Nonlinear performance analysis and prediction for robust low dose lung CTR01CA249538 · NCI · UNIVERSITY OF PENNSYLVANIA · PI GANG, JIANAN GRACE · 2021 to 2024
$2.0M
Ultra-high spatial resolution photon-counting CT with multiple focal spotsR01EB035908 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI Peter B Noel, JOSEPH Webster STAYMAN · 2025 to 2026
$1.2M
NCI NIH HHS R01 CA249538NIBIB NIH HHS R01 EB035908
6 · The paper itself

Abstract

Low-dose computed tomography (CT) remains a popular research topic with the advent of an increasing number of algorithmic solutions to control noise. One such approach that enforces data consistency through a model-based data likelihood term but that also includes a deep learning generative prior is Diffusion Posterior Sampling (DPS). This technique is formulated within a probabilistic framework and is capable of generating high-quality reconstructions under noisy and/or undersampled conditions. However, one major unanswered question is, given the opportunity to design a low-dose protocol, how should low dose be achieved - through sparse sampling or reduced fluence per projection. In this work, we conducted a simulation study and systematically investigated the impact of acquisition parameters - the number of views

Identifiers

PMID42017038
PMCPMC13095152

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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.