ImageCAS冠状动脉分割数据集
ImageCAS冠状动脉分割数据集提供冠状动脉CTA三维影像和冠脉树分割标注,数据模态为图像,可用于颈动脉疾病相关病例识别、诊断建模、分割检测、风险评估或临床研究复现。
基本信息
资源简介
ImageCAS 数据集包含冠状动脉CTA三维影像和冠脉树分割标注,可围绕颈动脉疾病(Carotid artery disease)开展病例筛选、特征提取、诊断分类、分割检测或预后分析。
https://github.com/XiaoweiXu/ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-CT
arXiv 论文 →下载信息
注册下载
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使用方式
数据集获取
git clone https://github.com/XiaoweiXu/ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-CT.git
curl -L -o repo.zip https://github.com/XiaoweiXu/ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-CT/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录(使用方式)
ImageCAS-A-Large-Scale-Dataset-and-Benchmark-for-Coronary-Artery-Segmentation-based-on-Computed-Tomo
This dataset contains about 1000 3D CTA images, which is considerably larger than the existing public datasets.
On the other hand, we also propose a benchmark based on the proposed dataset, in which we have not only implemented several typical existing methods but also proposed a strong baseline method.
An official data split is also prepared for fair comparison.
HIGHLIGHT 20230417: You may find some folders ending with (1), these are duplicated cases. We have updated the dataset to discard these duplicate cases. Please send me emails about this issue to get the link of the latest dataset.
HIGHLIGHT 20231101: We have deployed the dataset on Kaggle https://www.kaggle.com/xiaoweixumedicalai/datasets?scroll=true!
Please send emails to me xiao.wei.xu@foxmail.com for the link and the password to download the dataset and the benchmark.
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 颈动脉疾病 的高质量、多模态真实临床数据定制解决方案。




