ArticleSensors (Basel, Switzerland)2024
The Framework of Quantifying Biomarkers of OCT and OCTA Images in Retinal Diseases.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Hematopoietic stem and progenitor cells derived platelet lysate promotes diabetic wound healing.Molecular medicine (Cambridge, Mass.) · 2026Article
- Evaluation of classification performance for six types of fundus diseases in OCT images based on multi-source training strategy.Frontiers in medicine · 2026Article
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Authors and funding
4 authors.
Funding
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Abstract
Despite the significant advancements facilitated by previous research in introducing a plethora of retinal biomarkers, there is a lack of research addressing the clinical need for quantifying different biomarkers and prioritizing their importance for guiding clinical decision making in the context of retinal diseases. To address this issue, our study introduces a novel framework for quantifying biomarkers derived from optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images in retinal diseases. We extract 452 feature parameters from five feature types, including local binary patterns (LBP) features of OCT and OCTA, capillary and large vessel features, and the foveal avascular zone (FAZ) feature. Leveraging this extensive feature set, we construct a classification model using a statistically relevant
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Registered trials
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