卒中结局优化项目数据集
该数据集是一个包含急性中风患者多模态临床数据的公开医学研究资源，主要数据内容包括去标识化的医学影像、行为测量指标以及人口统计学信息，数据模态涵盖神经影像、行为测量和临床表格，主要用于支持神经影像数据处理流程的开发、教育以及构建符合BIDS标准的临床数据处理管道。
基本信息
资源简介
卒中结局优化项目数据集
【数据集背景】
本数据集源站标题为《OpenNeuroDatasets/ds004889》。源站首次发布：2023-12-20。
【数据内容】
源站原始描述：OpenNeuro dataset - Stroke Outcome Optimization Project (SOOP) # Stroke Outcome Optimization Project (SOOP) ## Overview This dataset includes anonymized images, behavioral measures and demographic details from a cohort of individuals from South Carolina with acute stroke. The fully BIDS-compatible dataset is fully anonymized, allowing public sharing which is vital for education and development of BIDS pipelines that are capable of processing clinical datasets. Along with its companion chronic Ap…
【获取与许可】
源站页面：https://github.com/OpenNeuroDatasets/ds004889
【使用注意】
· 源站最后修改于 2026-08-05，引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
git clone https://github.com/OpenNeuroDatasets/ds004889.git
curl -L -o repo.zip https://github.com/OpenNeuroDatasets/ds004889/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录（使用方式）
Stroke Outcome Optimization Project (SOOP)
Overview
This dataset includes anonymized images, behavioral measures and demographic details from a cohort of individuals from South Carolina with acute stroke. The fully BIDS-compatible dataset is fully anonymized, allowing public sharing which is vital for education and development of BIDS pipelines that are capable of processing clinical datasets. Along with its companion chronic Aphasia Recovery Cohort (ARC), these features complement existing repositories of [acute](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444746/ and chronic stroke.
Data Contents
participants.tsv- List of subject IDs, demographic variables, and impairment measures. Note that many variables are generalized to meet International Safe Harbor Privacy Principles.Subject Directories- MRI data directories for each subject. Note that sequence protocols and diffusion derivative formula vary between individuals. See the individual BIDS JSON sidecars included with each image for specific details.anat- T1w and T2w-FLAIR anatomical imagesdwi- Diffusion weighted Trace and apparent diffusion coefficient (ADC) images
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。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务？立即联系我们获取专业方案。
