Evidence map›Paper›PMID 42337987›Full record

ArticleJournal of biophotonics2026

Using Principal Components Analysis to Visualize Motion and Mitigate Artifacts in Dynamic Optical Coherence Tomography.

Alejandro Martínez Jiménez, Adrian Bradu

Abstract read
In one paragraph

Article in Journal of biophotonics, 2026. 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
–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

0 citing papers in PubMed.

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

2 authors.

Alejandro Martínez JiménezApplied Optics Group, School of Engineering, Mathematics and Physics, University of Kent, Canterbury, UK.
Adrian BraduApplied Optics Group, School of Engineering, Mathematics and Physics, University of Kent, Canterbury, UK.ORCID 0000-0002-6890-1599

Funding

Academy of Medical Sciences SBF007\100162Ministerio de Ciencia Innovacion y Universidades BG24/00089Royal Sociey RGS/R1/221324
6 · The paper itself

Abstract

Dynamic Optical Coherence Tomography (DOCT) is an advanced imaging technique that uses temporal fluctuations in OCT signals to improve contrast and enhance visualization of dynamic processes such as motion and metabolic activity. Although various methods for implementing the DOCT algorithm have been proposed, the use of Principal Component Analysis (PCA), a commonly used technique in medical imaging, remains relatively underexplored in this area. Our study demonstrates that selecting only the most significant principal components in PCA can substantially reduce artifacts from strong specular reflections, particularly when high-numerical-aperture microscope objectives are used. Furthermore, by using a small number of principal components, we can isolate movement within the sample, successfully reconstruct volumetric images, and create thin, histology-like sections of bovine kidney tissue, avoiding the need for complex, time-consuming techniques used in clinical histopathology.

Indexed as

ArtifactsImage Processing, Computer-AssistedPrincipal Component AnalysisTomography, Optical CoherenceAnimalsCattleKidneyMotionMovementdynamic OCThistopathologyoptical coherence tomographyprincipal component analysis

Identifiers

PMID42337987
PMCPMC13291352

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.