医学影像数据集|数据分析数据集

数据集获取

git clone https://github.com/Luffy03/Large-Scale-Medical.git

curl -L -o repo.zip https://github.com/Luffy03/Large-Scale-Medical/archive/refs/heads/main.zip
unzip repo.zip

数据集大小约 7086.08 GB。

源站 README 摘录（使用方式）

Quick Start

• Models: 31M~1.2B params of pre-trained models.
• Downstream: 50+ tasks implementations (segmentation, classification, registration, vision-language).
• Datasets:
• • PreCT-160K: The existing largest dataset in this field: 160K CT volumes
• • VoComni: 20K volumes with pseudo labels (20 organ & tumor classes)
• Pre-training:
• • Fully-supervised: Pre-training with labeled data
• • Self-supervised: Pre-training with unlabeled data
• • Semi-supervised: Pre-training with labeled and unlabeled data
• • Omni-supervised: Pre-training with labeled and unlabeled data
• CVPR version
• 公众号

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。

完整仓库：github.com/Luffy03/Large-Scale-Medical