Evidence map›Paper›PMID 30625170›Full record

ArticlePloS one2019

cellSTORM-Cost-effective super-resolution on a cellphone using dSTORM.

Benedict Diederich, Patrick Then, Alexander Jügler, Ronny Förster, Rainer Heintzmann

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Nanorulers for Super-Resolution Microscopy.Chembiochem : a European journal of chemical biology · 2026
    Review
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  15. Super-resolution microscopy: a brief history and new avenues.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
    Article
  16. Review
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  18. High-resolution radioluminescence microscopy of FDG uptake in an engineered 3D tumor-stoma model.European journal of nuclear medicine and molecular imaging · 2021
    Article
  19. Article
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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

5 authors.

Benedict DiederichLeibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, Jena, Germany.ORCID 0000-0003-0453-6286
Patrick ThenLeibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, Jena, Germany.
Alexander JüglerLeibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, Jena, Germany.
Ronny FörsterLeibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, Jena, Germany.
Rainer HeintzmannLeibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, Jena, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High optical resolution in microscopy usually goes along with costly hardware components, such as lenses, mechanical setups and cameras. Several studies proved that Single Molecular Localization Microscopy can be made affordable, relying on off-the-shelf optical components and industry grade CMOS cameras. Recent technological advantages have yielded consumer-grade camera devices with surprisingly good performance. The camera sensors of smartphones have benefited of this development. Combined with computing power smartphones provide a fantastic opportunity for "imaging on a budget". Here we show that a consumer cellphone is capable of optical super-resolution imaging by (direct) Stochastic Optical Reconstruction Microscopy (dSTORM), achieving optical resolution better than 80 nm. In addition to the use of standard reconstruction algorithms, we used a trained image-to-image generative adversarial network (GAN) to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance directly on the smartphone. We believe that "cellSTORM" paves the way to make super-resolution microscopy not only affordable but available due to the ubiquity of cellphone cameras.

Indexed as

SmartphoneAlgorithmsImage Processing, Computer-AssistedMachine LearningMicroscopy, FluorescenceOptical Imaging

Identifiers

PMID30625170
PMCPMC6326471

What OpenQuestion holds

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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.