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license: apache-2.0
tags:
- multimodal
- ophthalmology
- OCT
- benchmark
- medical
- visual question answering
---
# π€ OCT-Bench

To comprehensively evaluate Multimodal Large Language Models (MLLMs) on optical coherence tomography (OCT) image understanding, we introduce **OCT-Bench**, a comprehensive benchmark that follows the real-world clinical interpretation workflow from **visual perception**, **medical cognition**, to **clinical reasoning**.
OCT-Bench contains **10,076 expert-verified multiple-choice questions** constructed from **4,137 OCT images** collected from **seven public datasets**. The benchmark establishes a hierarchical capability taxonomy consisting of **3 capability dimensions**, **9 capability groups**, and **20 fine-grained tasks**, covering imaging attributes, retinal anatomy, lesion characteristics, disease diagnosis, treatment planning, and prognostic management.
We benchmark **20 representative MLLMs**, including proprietary models, open-source general-purpose models, and medical-domain models, providing a comprehensive evaluation of OCT understanding capabilities.
For detailed usage and instructions, please refer to the [GitHub page](https://github.com/baochenfu/OCT-Bench).
You can download **OCT-Bench**. The expected directory structure is:
OCT-Bench
βββ images
β βββ OCT5K
β βββ OCTDL
β βββ ...
βββ VQA
βββ T01_VQA.jsonl
βββ T02_VQA.jsonl
βββ ...
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