BEGIN 新型影像生物标志物

数据集获取

源站：https://clinicaltrials.gov/study/NCT05517655

标准获取流程：

1. 访问源站链接，注册/登录账号；
2. 进入数据集详情页，按页面指引申请权限或直接下载；
3. 部分平台提供 SDK，例如：
   • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
   • ModelScope: pip install modelscope 后 modelscope download
   • 天池: 登录后页面提供直链下载
     以源站「数据下载/使用文档」页面为准。

数据说明

Conditions: Cystic Fibrosis. The overall hypothesis is that multi-organ MRI will provide more sensitive, robust outcome measures in young CF patients than traditional measures employed in the BEGIN study and that these novel measures will be more sensitive to treatment effects, tested here by comparison before and after triple-combination modulator therapy. By understanding the nature of early lung obstruction and characteristic changes in the liver and pancreas over time, we continue to lay the groundwork for more personalized medicine in the future. Assessing treatment response and clinical benefit in children with CF who are clinically normal per standard outcomes (e.g., spirometry, pancreatic function) will become paramount as triplecombination therapy is extended to younger patients with milder CF clinical presentation than their historic peers. Here the sensitivity and profile free of ionizing-radiation exposure of MRI can be leveraged to follow an individual with CF over time to quantify changes with therapy-with additional spatial resolution unavailable from standard clinical testing.

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。