Evidence map›Paper›PMID 30194338›Full record

ArticleScientific reports2018

Single-shot memory-effect video.

Xiaohan Li, Andrew Stevens, Joel A Greenberg, Michael E Gehm

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Xiaohan LiDepartment of Electrical and Computer Engineering, Duke University, Box 90291, Durham, NC, 27708, United States.
Andrew StevensDepartment of Electrical and Computer Engineering, Duke University, Box 90291, Durham, NC, 27708, United States.
Joel A GreenbergDepartment of Electrical and Computer Engineering, Duke University, Box 90291, Durham, NC, 27708, United States.
Michael E GehmDepartment of Electrical and Computer Engineering, Duke University, Box 90291, Durham, NC, 27708, United States. michael.gehm@duke.edu.ORCID http://orcid.org/0000-0003-4163-749X

Funding

DOD | Defense Advanced Research Projects Agency (DARPA) HR0011-16-C-0027
6 · The paper itself

Abstract

Imaging through opaque scattering media is critically important in applications ranging from biological and astronomical imaging to metrology and security. While the random process of scattering in turbid media produces scattered light that appears uninformative to the human eye, a wealth of information is contained in the signal and can be recovered using computational post-processing techniques. Recent studies have shown that statistical correlations present in the scattered light, known as 'memory effects', allow for diffraction-limited imaging through opaque media without detailed knowledge of (or access to) the source or scatterer. However, previous methods require that the object and/or scatterer be static during the measurement. We overcome this limitation by combining traditional memory effect imaging with coded-aperture-based computational imaging techniques, which enables us to realize for the first time single-shot video of arbitrary dynamic scenes through dynamic, opaque media. This has important implications for a wide range of real-world imaging scenarios.

Identifiers

PMID30194338
PMCPMC6128846

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.