Fundus-MMBench

Benchmark for paper Constructing Ophthalmic MLLM for Positioning-diagnosis Collaboration Through Clinical Cognitive Chain Reasoning

🚨 Important: This benchmark is for academic research only.

Dataset Viewer Notice

🚨 The dataset viewer above only shows a preview of the first 10 rows from the dataset intending to provide a quick look at the data structure. The total number of data in the dataset is 620. To access the complete dataset, please download the full tsv file.

Introduction

The number of test samples for each task category of Fundus-MMBench is 20. It consists of 31 fine-grained tasks covering three core clinical domains: region-based object recognition (e.g., optic disc identification), disease classification (e.g., glaucoma vs. non-glaucoma diagnosis), and severity grading (e.g., diabetic retinopathy severity assessment).

Usage

You can run the evaluation on Fundus-MMBench using open-compass/VLMEvalKit. Note that Fundus-MMBench(tsv version) is not officially supported, but can be regarded as a Custom MCQ dataset.

Data Source

Dataset Name	Data Source URL
Diaretdb1	https://www.kaggle.com/datasets/nguyenhung1903/diaretdb1-v21
drishtiGS	https://www.kaggle.com/datasets/lokeshsaipureddi/drishtigs-retina-dataset-for-onh-segmentation
IDRiD	https://ieee-dataport.org/open-access/indian-diabetic-retinopathy-image-dataset-idrid
REFUGE	https://refuge.grand-challenge.org/REFUGE2018/
e-ophtha	https://www.adcis.net/en/third-party/e-ophtha/
Naikai OIA-DDR	https://github.com/nkicsl/DDR-dataset
ROC training	https://roc.grand-challenge.org/
BRSET	https://physionet.org/content/brazilian-ophthalmological/1.0.0/
PALM	https://ieee-dataport.org/documents/palm-pathologic-myopia-challenge
Glaucoma_fundus	https://drive.google.com/file/d/18vSazOYDsUGdZ64gGkTg3E6jiNtcrUrI/view
PAPILA	https://drive.google.com/file/d/1JltYs7WRWEU0yyki1CQw5-10HEbqCMBE/view
Retina	https://drive.google.com/file/d/1vdmjMRDoUm9yk83HMArLiPcLDk_dm92Q/view
JSIEC	https://drive.google.com/file/d/1q0GFQb-dYwzIx8AwlaFZenUJItix4s8z/view
MESSIDOR2	https://drive.google.com/file/d/1vOLBUK9xdzNV8eVkRjVdNrRwhPfaOmda/view
APTOS2019	https://drive.google.com/file/d/162YPf4OhMVxj9TrQH0GnJv0n7z7gJWpj/view
In-house

We would like to thank these contributions.