Evidence map›Paper›PMID 42433593›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2026

Optical Coherence Tomography Harmonization via Dual Diffusion Implicit Bridges.

Shuwen Wei, Samuel W Remedios, Blake E Dewey, Zhangxing Bian, Shimeng Wang, Junyu Chen, Yihao Liu, Bruno Jedynak, Tin Y A Liu, Shiv Saidha and 3 more

Abstract read
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In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2026. 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

13 authors.

Shuwen WeiDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Samuel W RemediosDepartment of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
Blake E DeweyDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
Zhangxing BianDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Shimeng WangDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Junyu ChenDepartment of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA.
Yihao LiuDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Bruno JedynakDepartment of Mathematics and Statistics, Portland State University, Portland, OR 97201, USA.
Tin Y A LiuDepartment of Ophthalmology, Wilmer Eye Institute, Baltimore, MD 21287, USA.
Shiv SaidhaDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
Peter A CalabresiDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
Jerry L PrinceDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Aaron CarassDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

Funding

OCT and OCTA image processing for retinal assessment of people with MSR01EY032284 · NEI · JOHNS HOPKINS UNIVERSITY · PI PRINCE, JERRY L · 2021 to 2024
$1.8M
NEI NIH HHS R01 EY032284
6 · The paper itself

Abstract

Image harmonization (IH) makes images from different domains consistent, enabling multi-domain comparison with reliable quantitative measurements. Optical coherence tomography (OCT) could benefit from IH, as variations in OCT systems cause significant discrepancies in image quality due to speckle and noise. However, IH approaches typically rely on paired images during the training phase, and such images are not available in OCT data due to sparse image acquisition. A Schrödinger bridge (SB) finds an optimal coupling between arbitrary probability spaces with respect to a reference path measure and can be applied to unpaired IH. SBs are the core of many generative diffusion models, when one of the probability spaces is easy to sample from (i.e., Gaussian). SBs have been applied to natural images for image-to-image translation; however, they have not been applied to OCT IH because a SB does not guarantee anatomical consistency. In this paper, we use a dual diffusion implicit bridge (DDIB) for OCT IH, which finds independent SBs between arbitrary domains and a common Gaussian probability space. We generalize the assumption of DDIB and use segmentation masks as a condition to improve anatomical consistency. We conduct DDIB experiments with and without segmentation masks as a condition and analyze performance in terms of anatomical consistency and harmonization quality. The method does not require any paired training data and can in principle be quickly adapted to new domains.

Indexed as

dual diffusion implicit bridgegenerative diffusion modelimage harmonizationOptical coherence tomographySchrödinger bridge

Identifiers

PMID42433593
PMCPMC13352811

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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.