Evidence map›Paper›PMID 42321326›Full record

ArticleScientific reports2026

Spatiotemporal information fusion for photon-level dynamic imaging.

Changzhi Yu, Shuangping Han, Chengbing Qin, Kai Song, Hongrui Liu, Pengyu Zan, Ao Li, Yaoxing Bian, Liantuan Xiao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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

9 authors.

Changzhi YuCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Shuangping HanCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China. hanshuangping@tyut.edu.cn.
Chengbing QinShanxi Key Laboratory of Precision Measurement Physics, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Kai SongCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Hongrui LiuCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Pengyu ZanCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Ao LiCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Yaoxing BianCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China.
Liantuan XiaoCollege of Physics and Optoelectronics Engineering, Taiyuan University of Technology, Taiyuan, 030024, Shanxi, China. xlt@sxu.edu.cn.

Funding

National Key Research and Development Program of China 2022YFA1404201National Natural Science Foundation of China 62305239National Natural Science Foundation of China 62505214National Natural Science Foundation of China U22A2091National Natural Science Foundation of China U23A20380Shanxi Provincial Basic Research Program Project 202203021222107Shanxi Provincial Basic Research Program Project 202203021222133
6 · The paper itself

Abstract

In the photon-starved regime, dynamic reconstructions often exhibit attenuated contrast, loss of fine structure, and temporal flicker, which obstruct high-frame-rate, high-fidelity imaging. We present PhotonST-Net, a spatiotemporal deep reconstruction network that fuses spatial structure with inter-frame dependencies through a frame-difference-aware architecture, thereby enforcing temporal coherence and restoring high-frequency detail at ultra-low photon counts. Operating at a sampling ratio as low as 2

Indexed as

Block compressive sensing imagingPhoton-level imagingSpatiotemporal fusion network

Identifiers

PMID42321326
PMCPMC13550490

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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.