Name: Neurite-OASIS
Creator: adalca

基本信息

模态

医学影像

大小

0.00007 GB

创建/更新时间

2024-05-20

版本

master

资源简介

Neurite-OASIS

【数据集背景】

本数据集源站标题为《adalca/medical-datasets》。源站首次发布：2019-02-26。

【数据内容】

源站原始描述：tracking medical datasets, with a focus on medical imaging # List of Medical (Imaging) Datasets I maintain this list mostly as a personal braindump of interesting medical datasets, with a focus on medical imaging. Rather than try to group / cluster datasets, I''m going to try to maintain a set of keywords for each. See commit log for a list of additions over time. Please feel free to contribute! **Disclaimer**: please remember to solve real clinical problems ☺ ## Datasets processed by us ### Neur…

【主题与分类】

主题标签：collection、datasets、imaging、learning、list、medical、medical-imaging。

【适用方向】

影像类数据可用于医学图像分析模型（检测、分割、分类）的训练与评测，也可用于标注质量与成像参数相关性的研究。

【获取与许可】

源站页面：https://github.com/adalca/medical-datasets

【使用注意】

· 源站最后修改于 2025-03-28，引用时请注意版本时效。

原始链接

https://github.com/adalca/medical-datasets

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

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。

免费样本无法满足模型训练要求？千方提供经三甲医院脱敏、带病理回证与专家标注的商业级专病数据集。

去商城查看获取定制方案

使用方式

数据集获取

git clone https://github.com/adalca/medical-datasets.git

curl -L -o repo.zip https://github.com/adalca/medical-datasets/archive/refs/heads/master.zip
unzip repo.zip

源站 README 摘录（使用方式）

MASSIVE

Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation
8000 diffusion-weighted volumes
10 3D FLAIR, T1-, and T2-weighted datasets of a single healthy subject
Keywords: large, MRI

AOMIC: the Amsterdam Open MRI Collection

1000+ fMRI and other modalities subjects with annotated event files; raw and preprocessed
Keywords: medium, fMRI

MRIdata

List of mri k-space datasets

Cancer Imaging Archive: LDCT

601 series of CT projection data, reconstructed images, and clinical data reports
Keywords: medium, CT, reconstruction

Brain MRI LGG FLAIR abnormality segmentation

Brain MRI images together with manual FLAIR abnormality segmentation masks
110 subjects from TCIA LGG collection with lower-grade glioma cases
Keywords: medium, brain, MRI, segmentation, LGG, FLAIR

Studyforrest

Few subjects, but many modalities (T1,T2,SWI,Angio,DWI, fMRI during Forrest Gump at 3T (audio+visual+eyetracking+physio) and 7T (audio+physio only), some audio tasks, and other important visual tasks)
Keywords: small, multi-modal

Lung Image Database Consortium

LIDC-IDRI consists of diagonstic and lung cancer screening CTs.
1018 cases with some Radiologist Annotations/Segmentations and nodule counts
Also available through LUng Nodule Analysis (LUNA) challenge
Keywords: large, CT, labels

Breast Cancer MRI Dataset

922 breast cancer patients publicly available for machine learning and clinical research.
Contains breast MRIs, clinical, demographics, pathology, treatment, outcomes, and genomic data as well as image annotations (locations) and features.
Keywords: large, MRI, labels

UK Biobank

[All imaging](http://biobank.ctsu.ox.ac.uk/crystal/search.cgi?wot=2&srch=imaging&sta0=on&sta1=on&sta2=on&sta3=on&sta4=on&str0=on&str3=on&fit0=on&fit10=on

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