A Brazilian Multilabel Ophthalmological Dataset (BRSET)

The Brazilian Multilabel Ophthalmological Dataset (BRSET) is a multi-labeled ophthalmological dataset designed to improve scientific community development and validate machine learning models. In ophthalmology, ancillary exams support medical decisions and can be used to develop algorithms; however, the availability and representativeness of ophthalmological datasets are limited. This dataset consists of 16,266 images from 8,524 Brazilian patients. Demographics, macula, optic disc, and vessels anatomical parameters, focus, illumination, image field, and artifacts as quality control, and multi-labels are included alongside color fundus retinal photos. This dataset enables computer vision models to predict demographic characteristics and multi-label disease classification using retinal fundus photos.

巴西多标签眼科数据集（BRSET）系一项旨在促进科学界发展并验证机器学习模型的多标签眼科数据集。在眼科领域，辅助检查支持医疗决策，并可用于算法开发；然而，眼科数据集的可用性和代表性有限。该数据集包含来自8,524位巴西患者的16,266幅图像。其中包含人口统计学、黄斑、视盘和血管解剖参数、焦点、照明、图像视野、伪影作为质量控制以及多标签。此数据集使计算机视觉模型能够利用视网膜眼底照片预测人口统计学特征和多标签疾病分类。

搜集汇总

背景与挑战

背景概述

BRSET是一个包含16,266张视网膜眼底照片的多标签眼科数据集，来自8,524名巴西患者，旨在支持机器学习模型的开发和验证。数据集提供了详细的人口统计学、解剖学和质量控制参数，以及多种眼科疾病的分类标签，填补了中低收入国家在眼科数据集中的代表性不足问题。