多发性硬化症数据集仓库
该数据集是一个专注于多发性硬化症(MS)的医学影像资源库,主要包含MRI图像模态,旨在为研究人员提供公开可访问的数据集,以支持多发性硬化症的分割、分类及疾病分析研究,适用于医学图像处理和神经科学领域的应用。

基本信息
资源简介
多发性硬化症数据集仓库
【数据集背景】
本数据集源站标题为《Fatimaxox/MS-Datasets-Sparks》。源站首次发布:2024-04-24。
【数据内容】
源站原始描述:# MS Datasets Repository Welcome to the MS Datasets Repository! This repository is dedicated to showcasing datasets used in both segmentation and classification problems related to Multiple Sclerosis (MS). Here, researchers and individuals interested in MS can easily access various datasets containing MRI images. ## MS Segmentation ### Dataset 1: Brain MRI Dataset of MS with Consensus Manual Lesion Segmentation and Patient Meta Information - **Source:** Baghdad Teaching Hospital - **Number of Su…
【获取与许可】
源站页面:https://github.com/Fatimaxox/MS-Datasets-Sparks
【使用注意】
· 源站最后修改于 2024-04-28,引用时请注意版本时效。
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/Fatimaxox/MS-Datasets-Sparks.git
curl -L -o repo.zip https://github.com/Fatimaxox/MS-Datasets-Sparks/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录(使用方式)
MS Datasets Repository
Welcome to the MS Datasets Repository! <br>
This repository is dedicated to showcasing datasets used in both segmentation and classification problems related to Multiple Sclerosis (MS). <br>
Here, researchers and individuals interested in MS can easily access various datasets containing MRI images.
MS Segmentation
Dataset 1: Brain MRI Dataset of MS with Consensus Manual Lesion Segmentation and Patient Meta Information
- Source: Baghdad Teaching Hospital
- Number of Subjects: 60 patients
- MRI Sequences Included: T1, T2, and Flair
- Year of Publication: 2022
- Data Type: NIFIT
Dataset 2: ISBI2015 MS Dataset or MS Longitudinal Challenge DataSet
- Source: Johns Hopkins University and Johns Hopkins Hospital
- Number of Subjects: 20 cases
- MRI Sequences Included: T1, T2, MPRAGE, Flair, and PD
- Year of Publication: 2015
- Data Type: NIFIT
Dataset 3: Multiple Sclerosis 2016 Lesion
- Number of Subjects: 53 with 10 cases
- MRI Sequences Included: T1, T2, Flair, and DP
- Year of Publication: 2016
- Data Type: NIFIT
Dataset 4: 2008 MICCAI MS Lesion Segmentation Challenge
- Number of Subjects: 45 with 5 cases
- MRI Sequences Included: T1, T2, Flair
- Last Modified: 2016
- Data Type: NHDR
Dataset 5: MICCAI 2021 - Longitudinal Multiple Sclerosis Lesion Segmentation Challenge
- Source: French Registry on Multiple Sclerosis
- Number of Subjects: 100 with 40 cases
- MRI Sequence Included: Flair
- Year of Publication: 2021
- Data Type: NIFIT
MS Classification
For classification, a local Saudi dataset obtained from King Fahad Specialists Hospital was utilized. A total of 229 patients participated, with MRI orientation covering Brain (Axial, Coronal, Sagittal) and Spinal cord. The MRI sequences included T1, T2, and FLAIR.
Additionally, other resources were utilized:
- Normal cases taken from Brain Tumor MRI Images - 17 Classes with 50 samples taken from T1, T2.
- Not MS cases from Brain Tumor MRI Dataset with 263 samples for the 3 types of tumor.
Contributors
This repository was made by Sparks Team. <br>
MSolutions
🧠🔬📊
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。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




