Evidence map›Paper›PMID 37159237›Full record

ArticleNanoscale2023

Spatial resolution enhancement in photon-starved STED imaging using deep learning-based fluorescence lifetime analysis.

Yuan-I Chen, Yin-Jui Chang, Yuansheng Sun, Shih-Chu Liao, Samantha R Santacruz, Hsin-Chih Yeh

Abstract read
In one paragraph

Article in Nanoscale, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. A Chemigenetic Fluorescence Lifetime Biosensor for Dopamine Sensing.bioRxiv : the preprint server for biology · 2026
    Article
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  4. Review
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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.

Yuan-I ChenBiomedical Engineering, University of Texas at Austin, Austin, TX, USA. Tim.Yeh@austin.utexas.edu.
Yin-Jui ChangBiomedical Engineering, University of Texas at Austin, Austin, TX, USA. Tim.Yeh@austin.utexas.edu.
Yuansheng SunISS, Inc., 1602 Newton Drive, Champaign, IL, 61822, USA.
Shih-Chu LiaoISS, Inc., 1602 Newton Drive, Champaign, IL, 61822, USA.
Samantha R SantacruzBiomedical Engineering, University of Texas at Austin, Austin, TX, USA. Tim.Yeh@austin.utexas.edu.
Hsin-Chih YehBiomedical Engineering, University of Texas at Austin, Austin, TX, USA. Tim.Yeh@austin.utexas.edu.ORCID http://orcid.org/0000-0001-6654-5626

Funding

Developing an ultrafast fluorescence lifetime imaging ophthalmoscopy system for retinal imagingR21EY033106 · NEI · UNIVERSITY OF TEXAS AT AUSTIN · PI YEH, HSIN-CHIH · 2021 to 2022
$399k
Turning a sequence barcode into a spectral barcode for single-cell analysis.R21GM129617 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI FINKELSTEIN, ILYA J, YEH, HSIN-CHIH · 2019 to 2020
$398k
NEI NIH HHS R21 EY033106NIGMS NIH HHS R21 GM129617
6 · The paper itself

Abstract

As a super-resolution imaging method, stimulated emission depletion (STED) microscopy has unraveled fine intracellular structures and provided insights into nanoscale organizations in cells. Although image resolution can be further enhanced by continuously increasing the STED-beam power, the resulting photodamage and phototoxicity are major issues for real-world applications of STED microscopy. Here we demonstrate that, with 50% less STED-beam power, the STED image resolution can be improved up to 1.45-fold using the separation of photons by a lifetime tuning (SPLIT) scheme combined with a deep learning-based phasor analysis algorithm termed

Identifiers

PMID37159237
PMCPMC10460507

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Registered trials

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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.