Evidence map›Paper›PMID 37323823›Full record

ArticleOptica2023

Augmented light field tomography through parallel spectral encoding.

Zhaoqiang Wang, Tzung K Hsiai, Liang Gao

Abstract read
In one paragraph

Article in Optica, 2023. 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

3 authors.

Zhaoqiang WangDepartment of Bioengineering, University of California, Los Angeles, 410 Westwood Plaza, Los Angeles, California 90095, USA.ORCID 0000-0002-6507-6167
Tzung K HsiaiDepartment of Bioengineering, University of California, Los Angeles, 410 Westwood Plaza, Los Angeles, California 90095, USA.
Liang GaoDepartment of Bioengineering, University of California, Los Angeles, 410 Westwood Plaza, Los Angeles, California 90095, USA.

Funding

Shear Stress and Light-Sheets to Study Cardiac TrabeculationR01HL129727 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HSIAI, TZUNG K, MARSDEN, ALISON L · 2015 to 2024
$3.5M
Ultrafast BioimagingR35GM128761 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Liang Gao · 2018 to 2026
$3.2M
Kilohertz 3D Optical Mapping of Atrial Fibrillation in Beating Zebrafish HeartsR01HL165318 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GAO, LIANG, HSIAI, TZUNG K · 2022 to 2025
$2.2M
Integrating Volumetric Light-Field with Computational Fluid Dynamics to Study Myocardial Trabeculation and FunctionR01HL159970 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HSIAI, TZUNG K, MARSDEN, ALISON L · 2021 to 2024
$2.0M
NHLBI NIH HHS R01 HL129727NHLBI NIH HHS R01 HL159970NHLBI NIH HHS R01 HL165318NIGMS NIH HHS R35 GM128761
6 · The paper itself

Abstract

Snapshot recording of transient dynamics in three dimensions (3-D) is highly demanded in both fundamental and applied sciences. Yet it remains challenging for conventional high-speed cameras to address this need due to limited electronic bandwidth and reliance on mechanical scanning. The emergence of light field tomography (LIFT) provides a new solution to these long-standing problems and enables 3-D imaging at an unprecedented frame rate. However, based on sparse-view computed tomography, LIFT can accommodate only a limited number of projections, degrading the resolution in the reconstructed image. To alleviate this problem, we herein present a spectral encoding scheme to significantly increase the number of allowable projections in LIFT while maintaining its snapshot advantage. The resultant system can record 3-D dynamics at a kilohertz volumetric frame rate. Moreover, by using a multichannel compressed sensing algorithm, we improve the image quality with an enhanced spatial resolution and suppressed aliasing artifacts.

Identifiers

PMID37323823
PMCPMC10270672

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Registered trials

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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.