EyePACS人工智能青光眼筛查挑战赛轻量级版本2
该数据集包含眼底图像模态的数据,来源于EyePASC人工智能青光眼筛查挑战赛的轻量级版本2,主要用于机器学习模型对青光眼的检测和分析,支持医学影像分析、计算机辅助诊断以及人工智能在眼科疾病筛查中的研究与应用。
基本信息
资源简介
该数据集是EyePACS人工智能青光眼筛查挑战赛的轻量级版本2,专门用于机器学习模型对青光眼的检测和分析。数据集包含眼底图像数据,来源于公开的医学影像资源,旨在支持青光眼自动筛查算法的开发与评估,适用于医学影像分析、计算机辅助诊断及人工智能在眼科疾病筛查中的应用研究。
下载信息
注册下载
Tips: 该数据集需要在对应的数据源网站注册通过后,才能进行数据下载,注册有对应要求,或者需要收费。
暂未开放公开下载
Tips: 该数据集属于公开下载,应该可以免费公开下载。
免登录有偿下载
Tips: 该数据集 Qianfanghub 可以协助提供有偿下载服务,注意,服务不针对数据相关产权,只是技术服务费。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放千方医数集,医疗数据集部分,是为社区服务的公开医疗数据集搜索引擎,并不存储或者下载原始的任何数据。 如果您有其他医疗数据需求,可以和客服联系,或者下工单。我们有强大的三甲医疗机构帮助您提供个性化的医疗数据定制、采集、标注服务。
使用方式
数据集获取
git clone https://github.com/TheBeastCoding/glaucoma-dataset-metadata.git
curl -L -o repo.zip https://github.com/TheBeastCoding/glaucoma-dataset-metadata/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录(使用方式)
New Updates
- 01/01/2026 : Adding new dataset, Hillel Yaffe Glaucoma Dataset (HYGD), https://physionet.org/content/hillel-yaffe-glaucoma-dataset/1.0.0/ and Fundus-AVSeg [https://figshare.com/articles/dataset/Fundus-AVSeg/27938034?file=54093641]
- 08/03/24 : A new abstract is available to the public, introducing a novel approach to glaucoma detection: Assessment of Retinal Vasculature for Glaucoma Detection: A Comparative Analysis of Human Expertise and Deep Learning Algorithms.
- 05/15/24 : The EyePACS-light-V2 code folder on Kaggle has a new PyTorch template for quick and easy glaucoma detection setup. This model uses the lightweight MobileNetV3 and achieved a test accuracy of 92.6%: https://www.kaggle.com/code/deathtrooper/pytorch-easy-setup-for-glaucoma-detection-92-6
- 03/09/24 : EyePACS-light-V2 now has a 10.0 Kaggle usability score: supplemental metadata.csv file added to dataset.
- 01/20/24 : EyePACS-light-V2 preprocess high-level overview is now available on the Kaggle dataset link in the about section (scroll all the way down) if you are curious on how the dataset was derived
- 12/28/23 : EyePACS-light-V2 94.94% test accuracy benchmark using ConvNeXtTiny: https://www.kaggle.com/code/deathtrooper/benchmark-94-94-convnexttiny
- 12/12/23 : EyePACS-light-V2 is HERE!!! Be the first to benchmark your model with this improved dataset! Download from kaggle: https://www.kaggle.com/datasets/deathtrooper/glaucoma-dataset-eyepacs-airogs-light-v2/data
Citation Note
If you found this catalog helpful, please consider citing the following:
- Riley Kiefer, Muhammad Abid, Jessica Steen, Mahsa Raeisi Ardali, and Ehsan Amjadian. 2023. A Catalog of Public Glaucoma Datasets for Machine Learning Applications: A detailed description and analysis of public glaucoma datasets available to machine learning engineers tackling glaucoma-related problems using retinal fundus images and OCT images. In Proceedings of the 2023 7th International Conference on Information System and Data Mining (ICISDM ''23). Association for Computing Machinery, New York, NY, USA, 24–31. https://doi.org/10.1145/3603765.3603779
Public Glaucoma Dataset Catalog
[Help expand this repository by providing links/publications to new glaucoma datasets!]
Repository Table of Contents
- README.md : Glaucoma overview, relevant research, and dataset access links
- benchmark-eyepacs-airogs-light.md : Leader
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
精度瓶颈?数据缺失?
当前公开数据无法满足您的算法精度?千方提供针对 青光眼 的高质量、多模态真实临床数据定制解决方案。



