Glaucoma Detection and Structured OCT Report Generation via a Fine-tuned Multimodal Large Language Model.

The fine-tuned MM-LLM generated accurate clinical descriptions based on OCT imaging. The model achieved high accuracy in identifying image quality issues and detecting glaucoma. The model also provided sectoral descriptions of RNFL thinning to help support clinical OCT evaluation. This approach shows potential as a scalable tool for clinical decision support, but further validation across additional datasets is needed.

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Publication Details

Journal
PubMed
Published
2025-10-01
Primary Topic
Retinal Imaging and Analysis
Type
article
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OCT
article

Glaucoma Detection and Structured OCT Report Generation via a Fine-tuned Multimodal Large Language Model.

PubMed
Retinal Imaging and Analysis
article

Glaucoma Detection and Structured OCT Report Generation via a Fine-tuned Multimodal Large Language Model.

article en

Abstract

The fine-tuned MM-LLM generated accurate clinical descriptions based on OCT imaging. The model achieved high accuracy in identifying image quality issues and detecting glaucoma. The model also provided sectoral descriptions of RNFL thinning to help support clinical OCT evaluation. This approach shows potential as a scalable tool for clinical decision support, but further validation across additional datasets is needed.

PubMed
University of Alabama at Birmingham (US), University of California San Diego (US), New York Glaucoma Research Institute (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 35%
Retinal Imaging and Analysis
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Glaucoma Detection and Structured OCT Report Generation via a Fine-tuned Multimodal Large Language Model. · PubMed (2025) | TGRS Research Map | TGRS