Generalized Image Reconstruction in Optical Coherence Tomography Using Redundant and Non-Uniformly-Spaced Samples.

Karim Nagib, Biniyam Mezgebo, Namal Fernando, Behzad Kordi, Sherif S Sherif

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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.

Compressed Sensing for Biomedical Photoacoustic Imaging: A Review.Sensors (Basel, Switzerland) · 2024
Review
Deep learning segmentation of the tear fluid reservoir under the sclera lens in optical coherence tomography images.Biomedical optics express · 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.

Karim NagibDepartment of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Biniyam MezgeboDepartment of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Namal FernandoManitoba Hydro High Voltage Test Facility, Manitoba Hydro, Winnipeg, MB R3T 1Y6, Canada.

Behzad KordiDepartment of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Sherif S SherifDepartment of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we use Frame Theory to develop a generalized OCT image reconstruction method using redundant and non-uniformly spaced frequency domain samples that includes using non-redundant and uniformly spaced samples as special cases. We also correct an important theoretical error in the previously reported results related to OCT image reconstruction using the Non-uniform Discrete Fourier Transform (NDFT). Moreover, we describe an efficient method to compute our corrected reconstruction transform, i.e., a

Indexed as

AlgorithmsTomography, Optical CoherenceFourier AnalysisImage Processing, Computer-AssistedSignal-To-Noise Rationon-uniform discrete fourier transformoptical coherence tomographyredundant samples

Identifiers

PMID34770364

DOI10.3390/s21217057

PMCPMC8587445

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.