Evidence map›Paper›PMID 37638109›Full record

ArticleJournal of biomedical optics2023

Depth-dependent attenuation and backscattering characterization of optical coherence tomography by stationary iterative method.

Yaning Wang, Shuwen Wei, Jin U Kang

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2023. 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. Article
  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

3 authors.

Yaning WangJohns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.
Shuwen WeiJohns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.ORCID 0000-0001-8679-9615
Jin U KangJohns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.

Funding

Artificial intelligence Optical Coherence Tomography Guided Deep Anterior Lamellar Keratoplasty (AUTO-DALK)R01EY032127 · NEI · JOHNS HOPKINS UNIVERSITY · PI KANG, JIN U · 2021 to 2024
$1.6M
NEI NIH HHS R01 EY032127
6 · The paper itself

Abstract

Significance: Extracting optical properties of tissue [e.g., the attenuation coefficient ( Aim: Our aim is to develop a robust and accurate model that calculates depth-wise values of attenuation and backscattering fractions simultaneously from OCT signals. Furthermore, we aim to develop an attenuation compensation model for OCT images that utilizes the optical properties we obtained to improve the visual representation of tissues. Approach: Using the stationary iteration method under suitable constraint conditions, we derived the approximated solutions of Results: The preliminary validation was performed in the OCT A-line simulation and Monte Carlo modeling, and the subsequent experiment was conducted on multi-layer silicone-dye- Conclusions: Our proposed method was able to correct the estimation bias induced by the variations of

Indexed as

EyeTomography, Optical CoherenceAnimalsCattleComputer SimulationFemaleMonte Carlo MethodPhantoms, Imagingattenuation coefficientattenuation compensationbackscattering fractionmultiple scatteringoptical coherence tomographysingle scattering

Identifiers

PMID37638109
PMCPMC10449262

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.