Evidence map›Paper›PMID 36859879›Full record

ArticleOptics express2023

Overcoming the field-of-view to diameter trade-off in microendoscopy via computational optrode-array microscopy.

Ruipeng Guo, Reed Sorenson, Robert Scharf, Austin Koch, Andrew Groover, Leslie Sieburth, Steve Blair, Rajesh Menon

Open access · goldAbstract read
In one paragraph

Article in Optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 21% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

Ruipeng Guo
Reed Sorenson
Robert Scharf
Austin Koch
Andrew Groover
Leslie Sieburth
Steve Blair
Rajesh Menon
University of Utah · USUS Forest Service · US

Funding

Expanding field-of-view with reduced tissue displacement in micro-endoscopic computational imagingR21EY030717 · NEI · UNIVERSITY OF UTAH · PI BLAIR, STEVEN M, MENON, RAJESH · 2019 to 2019
$457k
NEI NIH HHS R21 EY030717
6 · The paper itself

Abstract

High-resolution microscopy of deep tissue with large field-of-view (FOV) is critical for elucidating organization of cellular structures in plant biology. Microscopy with an implanted probe offers an effective solution. However, there exists a fundamental trade-off between the FOV and probe diameter arising from aberrations inherent in conventional imaging optics (typically, FOV < 30% of diameter). Here, we demonstrate the use of microfabricated non-imaging probes (optrodes) that when combined with a trained machine-learning algorithm is able to achieve FOV of 1x to 5x the probe diameter. Further increase in FOV is achieved by using multiple optrodes in parallel. With a 1 × 2 optrode array, we demonstrate imaging of fluorescent beads (including 30 FPS video), stained plant stem sections and stained living stems. Our demonstration lays the foundation for fast, high-resolution microscopy with large FOV in deep tissue via microfabricated non-imaging probes and advanced machine learning.

Indexed as

AlgorithmsMicroscopyColoring AgentsMachine LearningColoring Agents

Identifiers

PMID36859879
PMCPMC10018790
OpenAlexW4312190457

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.