喉癌CT数据集

Name: 喉癌CT数据集
Creator: Deakin University, Australia and Kasturba Medical College, Manipal, India

该数据集包含1029个喉癌患者的CT扫描影像数据，数据模态为三维医学图像，提供了喉部区域的标准化感兴趣区域和全面的元信息，主要用于开发和评估3D深度学习模型在喉癌早期与晚期分期以及T4亚型分类任务中的性能，为临床决策支持和医学影像分析研究提供基准测试资源。

Deakin University, Australia and Kasturba Medical College, Manipal, India

arXiv

2025-10-13 更新

喉癌分类医学图像分析

基本信息

大小

0.78 GB

创建/更新时间

2025-10-13

版本

main

资源简介

喉癌CT数据集

【数据集背景】

本数据集源站标题为《funzi-son/LaryngealCT》。源站首次发布：2025-06-20。

【数据内容】

源站原始描述：# CT Data Preparation for Laryngeal CT Imaging Despite the rich body of research in head and neck cancer, laryngeal cancer imaging lacks a dedicated public dataset for model development and comparison. We introduce the first curated laryngeal cancer dataset derived from six prominent Cancer Image Archive (TCIA) collections. To support efficient model training and reduce computational overhead, we extracted 1 mm isotropic volumes centered on the laryngeal region, extending from the epiglottis to…

【获取与许可】

源站页面：https://github.com/funzi-son/LaryngealCT

【使用注意】

· 源站最后修改于 2026-07-08，引用时请注意版本时效。

原始链接

https://github.com/funzi-son/LaryngealCT

访问原始数据

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付，我们提供全链路闭环服务，让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持？联系我们获取定制方案。

帮我联系

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/funzi-son/LaryngealCT.git

curl -L -o repo.zip https://github.com/funzi-son/LaryngealCT/archive/refs/heads/main.zip
unzip repo.zip

源站 README 摘录（使用方式）

STEP 0: Download Datasets from https://www.cancerimagingarchive.net

We select images from six datasets in the Cancer Image Archive https://www.cancerimagingarchive.net. Downloading datasets from TCIA requires license to access Restriced Access data, which should be applied through proper channel. Users are encouraged to register and download 6 public datasets containing computed tomography (CT) scans of patients with confirmed head and neck cancer, including laryngeal cancer. The datasets include: RADCURE, Head-Neck-PET-CT, HEAD-NECK-RADIOMICS-HN1, HNSCC, Head-Neck-3DCT-RT, and QIN-HEADNECK. All imaging data and associated metadata were downloaded using the National Biomedical Imaging Archive (NBIA) Data Retriever. Clinical annotations included age, sex, tumour subsite, T-stage, and treatment type (surgery, radiotherapy, or chemoradiotherapy), when available. The stage-wise breakdown of the laryngeal cancer cases across the different datasets is summarized in table below.

After downloading RADCURE, Head-Neck-PET-CT, HEAD-NECK-RADIOMICS-HN1, HNSCC, Head-Neck-3DCT-RT, and QIN-HEADNECK, users should save them under the “data/tcia” folder. If the “tcia” folder does not exist under the “data” folder, please create one.

NOTE: Make sure you place the downloaded TCIA data folder into the “data” directory and rename it as “tcia”.

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