Evidence map›Paper›PMID 28437941›Full record

ArticleOptics express2017

Effect of scattering on coherent anti-Stokes Raman scattering (CARS) signals.

Janaka C Ranasinghesagara, Giuseppe De Vito, Vincenzo Piazza, Eric O Potma, Vasan Venugopalan

Abstract read
In one paragraph

Article in Optics express, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Modeling nonlinear optical microscopy in scattering media, part I. Propagation from lens to focal volume: tutorial.Journal of the Optical Society of America. A, Optics, image science, and vision · 2023
    Article
  2. Modeling nonlinear optical microscopy in scattering media, part II. Radiation from focal volume to far-field: tutorial.Journal of the Optical Society of America. A, Optics, image science, and vision · 2023
    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

5 authors.

Janaka C Ranasinghesagara
Giuseppe De Vito
Vincenzo Piazza
Eric O Potma
Vasan Venugopalan

Funding

Virtual Photonocs TechnologiesP41EB015890 · NIBIB · UNIVERSITY OF CALIFORNIA-IRVINE · PI VENUGOPALAN, VASAN · 2012 to 2017
$7.0M
NIBIB NIH HHS P41 EB015890
6 · The paper itself

Abstract

We develop a computational framework to examine the factors responsible for scattering-induced distortions of coherent anti-Stokes Raman scattering (CARS) signals in turbid samples. We apply the Huygens-Fresnel wave-based electric field superposition (HF-WEFS) method combined with the radiating dipole approximation to compute the effects of scattering-induced distortions of focal excitation fields on the far-field CARS signal. We analyze the effect of spherical scatterers, placed in the vicinity of the focal volume, on the CARS signal emitted by different objects (2μm diameter solid sphere, 2μm diameter myelin cylinder and 2μm diameter myelin tube). We find that distortions in the CARS signals arise not only from attenuation of the focal field but also from scattering-induced changes in the spatial phase that modifies the angular distribution of the CARS emission. Our simulations further show that CARS signal attenuation can be minimized by using a high numerical aperture condenser. Moreover, unlike the CARS intensity image, CARS images formed by taking the ratio of CARS signals obtained using x- and y-polarized input fields is relatively insensitive to the effects of spherical scatterers. Our computational framework provide a mechanistic approach to characterizing scattering-induced distortions in coherent imaging of turbid media and may inspire bottom-up approaches for adaptive optical methods for image correction.

Identifiers

PMID28437941
PMCPMC5462071

What OpenQuestion holds

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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.