Evidence map›Paper›PMID 40030438›Full record

ArticleIEEE transactions on bio-medical engineering2025

Unifying Structure and Function Towards a Comprehensive Macular Evaluation in Eye Disorders: A Multi-Modal Approach Using Microperimetry and Optical Coherence Tomography.

Rijul Saurabh Soans, Benjamin E Smith, Susana T L Chung

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2025. 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.

Rijul Saurabh Soans
Benjamin E Smith
Susana T L Chung

Funding

READING IN PERIPHERAL VISIONR01EY012810 · NEI · UNIVERSITY OF HOUSTON · PI CHUNG, SUSANA T · 2000 to 2017
$3.8M
Functional impact of fixational eye movements in central vision lossR21EY030253 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI CHUNG, SUSANA T · 2020 to 2021
$432k
NEI NIH HHS R01 EY012810NEI NIH HHS R21 EY030253
6 · The paper itself

Abstract

objectiveWe present a new automatic and comprehensive framework to evaluate retinal sub-layer thickness and visual sensitivity at precise retinal locations through multi-modal registration of confocal scanning laser ophthalmoscope (cSLO) images obtained separately from an optical coherence tomography (OCT) device and a microperimeter.

methodsWe map consecutive B-scans onto the cSLO images after accounting for eye motion. Next, we coarsely register the SLO-microperimetry and cSLO-OCT images using SIFT, followed by precise elastic image registration. Subsequently, we ensure the quality of the co-registered images through single-particle and object tracking of the warped microperimetry test locations. Finally, the retinal thickness is queried from the segmented retinal layers in the co-registered space. A manual mode involving projective transformation accounting for perspective distortions in the images arising from the two modalities is also included.

resultsValidation using retinal images of 8 adults with albinism, 16 adults with amblyopia, 3 adults with macular diseases, and 15 visually healthy adults showed results with excellent reliability.

conclusionThe proposed framework enables the evaluation of retinal thickness by utilizing precise structural and functional relationships of the eye through a self-assessing multi-tiered approach. SIGNIFICANCE: Our framework lays the foundation towards a comprehensive structure-function assessment of the macular region in various eye disorders.

Indexed as

Macula LuteaMultimodal ImagingRetinal DiseasesTomography, Optical CoherenceVisual Field TestsAdultFemaleHumansMaleMiddle AgedOphthalmoscopyRetinaYoung Adult

Identifiers

PMID40030438
PMCPMC12129051

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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.