Evidence map›Paper›PMID 30245813›Full record

ArticleLight, science & applications2018

A deep learning-enabled portable imaging flow cytometer for cost-effective, high-throughput, and label-free analysis of natural water samples.

Zoltán Gӧrӧcs, Miu Tamamitsu, Vittorio Bianco, Patrick Wolf, Shounak Roy, Koyoshi Shindo, Kyrollos Yanny, Yichen Wu, Hatice Ceylan Koydemir, Yair Rivenson and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Light, science & applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
12.5field-weighted citation impact, top 1% of its field
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

46 citing papers in PubMed, 178 citations in OpenAlex.

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  4. Varifocal Meta-Lens for Multifunctional Focusing and Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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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

11 authors at 2 institutions in 1 country.

Zoltán Gӧrӧcs *1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Miu Tamamitsu *1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Vittorio Bianco1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Patrick Wolf1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Shounak Roy1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.ORCID 0000-0001-7323-3268
Koyoshi Shindo1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Kyrollos Yanny2Bioengineering Department, University of California, Los Angeles, CA 90095 USA.
Yichen Wu1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Hatice Ceylan Koydemir1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Yair Rivenson1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.
Aydogan Ozcan1Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095 USA.ORCID 0000-0002-0717-683X
California NanoSystems Institute · USUniversity of California, Los Angeles · US

Funding

UCLA MSD ProgramR25GM055052 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BARBER, PAUL HENRY, HASSON, TAMA W. · 1996 to 2021
$9.2M
NIGMS NIH HHS R25 GM055052
6 · The paper itself

Abstract

We report a deep learning-enabled field-portable and cost-effective imaging flow cytometer that automatically captures phase-contrast color images of the contents of a continuously flowing water sample at a throughput of 100 mL/h. The device is based on partially coherent lens-free holographic microscopy and acquires the diffraction patterns of flowing micro-objects inside a microfluidic channel. These holographic diffraction patterns are reconstructed in real time using a deep learning-based phase-recovery and image-reconstruction method to produce a color image of each micro-object without the use of external labeling. Motion blur is eliminated by simultaneously illuminating the sample with red, green, and blue light-emitting diodes that are pulsed. Operated by a laptop computer, this portable device measures 15.5 cm × 15 cm × 12.5 cm, weighs 1 kg, and compared to standard imaging flow cytometers, it provides extreme reductions of cost, size and weight while also providing a high volumetric throughput over a large object size range. We demonstrated the capabilities of this device by measuring ocean samples at the Los Angeles coastline and obtaining images of its micro- and nanoplankton composition. Furthermore, we measured the concentration of a potentially toxic alga (

Identifiers

PMID30245813
PMCPMC6143550
OpenAlexW2889672357

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.