Evidence map›Paper›PMID 35284166›Full record

ArticleBiomedical optics express2022

Three-dimensional light-field microendoscopy with a GRIN lens array.

Tara M Urner, Andrew Inman, Benjamin Lapid, Shu Jia

Abstract read
In one paragraph

Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

Tara M UrnerWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.ORCID https://orcid.org/0000-0001-7030-9255
Andrew InmanWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.
Benjamin LapidWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.
Shu JiaWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.ORCID https://orcid.org/0000-0001-6854-7537

Funding

Toward Systems Biophotonics: Imaging Biology across High Dimensions and ScalesR35GM124846 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI Shu Jia · 2017 to 2026
$4.0M
NIGMS NIH HHS R35 GM124846
6 · The paper itself

Abstract

Optical endoscopy has emerged as an indispensable clinical tool for modern minimally invasive surgery. Most systems primarily capture a 2D projection of the 3D surgical field. Currently available 3D endoscopes can restore stereoscopic vision directly by projecting laterally shifted views of the operating field to each eye through 3D glasses. These tools provide surgeons with informative 3D visualizations, but they do not enable quantitative volumetric rendering of tissue. Therefore, advanced tools are desired to quantify tissue tomography for high precision microsurgery or medical robotics. Light-field imaging suggests itself as a promising solution to the challenge. The approach can capture both the spatial and angular information of optical signals, permitting the computational synthesis of the 3D volume of an object. In this work, we present GRIN lens array microendoscopy (GLAM), a single-shot, full-color, and quantitative 3D microendoscopy system. GLAM contains integrated fiber optics for illumination and a GRIN lens array to capture the reflected light field. The system exhibits a 3D resolution of ∼100 µm over an imaging depth of ∼22 mm and field of view up to 1 cm

Identifiers

PMID35284166
PMCPMC8884202

What OpenQuestion holds

Textmetadata
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.