Datasets:
metadata
license: apache-2.0
task_categories:
- image-text-to-text
tags:
- multimodal
- ophthalmology
- OCT
- benchmark
- medical
- visual question answering
π€ OCT-Bench
We introduce OCT-Bench, a comprehensive benchmark for evaluating Multimodal Large Language Models (MLLMs) on optical coherence tomography (OCT) image understanding. OCT-Bench comprises 10,076 expert-verified multiple-choice questions from 4,137 OCT images across seven public datasets and evaluates 3 capability dimensions, 9 capability groups, and 20 fine-grained tasks covering perception, cognition, and clinical reasoning. We benchmark 20 representative MLLMs, including proprietary, open-source, and medical-domain models, providing a comprehensive assessment of OCT understanding capabilities.
For detailed usage and instructions, please refer to the GitHub page.
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 ...
