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Article

An Artificial Intelligence Method for Phenotyping of OCT-Derived Thickness Maps Using Unsupervised and Self-supervised Deep Learning.

Journal of imaging informatics in medicine - 1 Feb 2026

Kazeminasab Saber, Sekimitsu Sayuri, Fazli Mojtaba, Eslami Mohammad, Shi Min, Tian Yu, Luo Yan, Wang Mengyu, Elze Tobias, Zebardast Nazlee

Abstract excerpt

The objective of this study is to enhance the understanding of ophthalmic disease physiology and genetic architecture through the analysis of optical coherence tomography (OCT) images using artificial intelligence (AI). We introduce a novel AI methodology that addresses the challenge of transferring OCT phenotypes across datasets. The approach employs unsupervised and self-supervised learning techniques to...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 40394321
DOI: 10.1007/s10278-025-01539-x
PMCID: PMC12921106

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

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