Evidence map›Paper›PMID 29226243›Full record

ArticleScience advances2017

Single-frame 3D fluorescence microscopy with ultraminiature lensless FlatScope.

Jesse K Adams, Vivek Boominathan, Benjamin W Avants, Daniel G Vercosa, Fan Ye, Richard G Baraniuk, Jacob T Robinson, Ashok Veeraraghavan

Open access · goldAbstract read
In one paragraph

Article in Science advances, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
21.2field-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

49 citing papers in PubMed, 201 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Learned lensless 3D camera.Optics express · 2022
    Article
  19. Article
  20. FlatNet: Towards Photorealistic Scene Reconstruction From Lensless Measurements.IEEE transactions on pattern analysis and machine intelligence · 2022
    Article
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

8 authors at 3 institutions in 1 country.

Jesse K AdamsApplied Physics Program, Rice University, 6100 Main Street, Houston, TX 77005, USA.ORCID 0000-0002-6767-3221
Vivek BoominathanDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.ORCID 0000-0003-4875-3135
Benjamin W AvantsDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.ORCID 0000-0003-1994-7096
Daniel G VercosaApplied Physics Program, Rice University, 6100 Main Street, Houston, TX 77005, USA.ORCID 0000-0002-6840-7208
Fan YeDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.ORCID 0000-0003-3248-9042
Richard G BaraniukDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.ORCID 0000-0002-0721-8999
Jacob T RobinsonApplied Physics Program, Rice University, 6100 Main Street, Houston, TX 77005, USA.ORCID 0000-0002-3509-3054
Ashok VeeraraghavanApplied Physics Program, Rice University, 6100 Main Street, Houston, TX 77005, USA.ORCID 0000-0001-5043-7460
NeoPhotonics (United States) · USRice University · USBaylor College of Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern biology increasingly relies on fluorescence microscopy, which is driving demand for smaller, lighter, and cheaper microscopes. However, traditional microscope architectures suffer from a fundamental trade-off: As lenses become smaller, they must either collect less light or image a smaller field of view. To break this fundamental trade-off between device size and performance, we present a new concept for three-dimensional (3D) fluorescence imaging that replaces lenses with an optimized amplitude mask placed a few hundred micrometers above the sensor and an efficient algorithm that can convert a single frame of captured sensor data into high-resolution 3D images. The result is FlatScope: perhaps the world's tiniest and lightest microscope. FlatScope is a lensless microscope that is scarcely larger than an image sensor (roughly 0.2 g in weight and less than 1 mm thick) and yet able to produce micrometer-resolution, high-frame rate, 3D fluorescence movies covering a total volume of several cubic millimeters. The ability of FlatScope to reconstruct full 3D images from a single frame of captured sensor data allows us to image 3D volumes roughly 40,000 times faster than a laser scanning confocal microscope while providing comparable resolution. We envision that this new flat fluorescence microscopy paradigm will lead to implantable endoscopes that minimize tissue damage, arrays of imagers that cover large areas, and bendable, flexible microscopes that conform to complex topographies.

Identifiers

PMID29226243
PMCPMC5722650
OpenAlexW2773515295

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.