Emory White Matter Hyperintensity Dataset
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The Emory White Matter Hyperintensity (WMH) Dataset is a retrospectively curated collection of defaced clinical brain MRI scans with expert manual WMH annotations, developed to support robust evaluation of WMH segmentation methods under real-world clinical heterogeneity. The dataset comprises 195 routine clinical MRI examinations acquired between 2006 and 2022 from 71 distinct scanners, spanning multiple vendors, magnetic field strengths, and acquisition protocols. This diversity reflects real-world clinical variability and enables systematic assessment of model generalizability and robustness. White matter hyperintensities were manually delineated by an experienced rater and reviewed under neuroradiologist supervision. The dataset includes fixed training and test splits, together with standardized participant- and scanner-level metadata, to facilitate reproducible benchmarking and fair comparison of WMH segmentation algorithms. All MRI images have been defaced, and no direct personal identifiers are included. Data Access Data access is managed through the Alzheimer's Disease Data Initiative (ADDI) AD Workbench. All requests for access to the Emory WMH Dataset must be submitted via: https://discover.alzheimersdata.org/catalogue/datasets/9f93737c-ecf2-4e62-a748-d626f6e84ec1 Related publication This dataset accompanies the peer-reviewed article: Benchmark white matter hyperintensity segmentation methods fail on heterogeneous clinical MRI: A new dataset and deep learning-based solutions Wu J, Brown JD, Hu R, Edwards PJ, Levey AI, Lah JJ, Qiu D. Journal of Imaging Informatics in Medicine. https://doi.org/10.1007/s10278-025-01808-9 Processing Pipeline A pre-configured Docker image for the Emory Robust WMH Segmentation pipeline is available at:https://hub.docker.com/r/emorycn2l/emory_robust_wmh It provides a standardized, fully reproducible environment for robust, automated WMH segmentation on heterogeneous clinical MRI (FLAIR and T1-weighted images). The included nnU-Net model was trained on the Emory White Matter Hyperintensity Dataset. Dataset organization The dataset is organized into fixed training and test splits with one directory per participant: emory_wmh_dataset/├── README.md├── train/│ └── sub-XXXXXXXX/│ ├── original/│ ├── preprocessed/│ └── wmh.nii.gz├── test/│ └── sub-XXXXXXXX/│ ├── original/│ ├── preprocessed/│ └── wmh.nii.gz└── participants.tsv Each participant is assigned a pseudonymous identifier (sub-XXXXXXXX). Imaging data and annotations For each participant, the dataset includes: Preprocessed images Defaced, N4 bias-corrected FLAIR image Defaced, N4 bias-corrected T1-weighted image co-registered to FLAIR space Original images Defaced FLAIR and T1-weighted images in native acquisition space Defacing mask for T1-weighted image Affine transformation matrix mapping native T1-weighted space to FLAIR space (FSL FLIRT format) WMH annotation Binary WMH segmentation mask aligned to preprocessed FLAIR space (0 = background, 1 = WMH) Metadata Participant- and scanner-level metadata are provided in participants.tsv and may include: Demographics and clinical variables (e.g., age, sex, diagnosis, etiology, cognitive scores) CSF biomarkers (when available) Scanner information, including anonymized scanner identifiers and magnetic field strength Dataset split designation (train or test) These metadata support stratified analyses across demographic, clinical, and acquisition-related factors. Privacy and data protection All images are defaced to remove facial features. Scanner identifiers are pseudonymized using a salted one-way cryptographic transform, preventing re-identification while preserving scanner-level analytical utility.
Emory白质高信号（White Matter Hyperintensity, WMH）数据集是一项回溯性整理的去面部标识临床脑部MRI扫描集，附带专家手动标注的WMH标签，旨在支持在真实世界临床异质性场景下对WMH分割方法进行可靠评估。 该数据集包含2006年至2022年间采集的195例常规临床MRI检查数据，来自71台不同型号的扫描仪，涵盖多个厂商、磁场强度及采集协议。这种多样性贴合真实临床场景的变异性，可用于系统性评估模型的泛化能力与鲁棒性。 白质高信号由经验丰富的标注员手动勾勒，并经神经放射学家审核。数据集提供固定的训练集与测试集划分，同时附带标准化的受试者及扫描仪层面元数据，以助力可复现的基准测试与WMH分割算法的公平对比。 所有MRI图像均已完成去面部标识处理，未包含直接的个人身份识别信息。 ## 数据访问 数据访问通过阿尔茨海默病数据倡议（Alzheimer's Disease Data Initiative, ADDI）AD工作台进行管理。所有申请使用Emory WMH数据集的请求均需通过以下链接提交： https://discover.alzheimersdata.org/catalogue/datasets/9f93737c-ecf2-4e62-a748-d626f6e84ec1 ## 相关发表文献 本数据集配套发表于同行评审期刊的论文： 《基准白质高信号分割方法在异质性临床MRI上表现欠佳：新数据集与基于深度学习的解决方案》 作者：Wu J、Brown JD、Hu R、Edwards PJ、Levey AI、Lah JJ、Qiu D 发表期刊：《医学影像信息学杂志》（Journal of Imaging Informatics in Medicine） DOI：10.1007/s10278-025-01808-9 ## 处理流程 面向Emory鲁棒WMH分割流程的预配置Docker镜像可在以下地址获取：https://hub.docker.com/r/emorycn2l/emory_robust_wmh。该镜像为异质性临床MRI（液体衰减反转恢复序列Fluid-Attenuated Inversion Recovery, FLAIR及T1加权图像T1-weighted image）的鲁棒自动WMH分割提供了标准化、完全可复现的运行环境。其中附带的nnU-Net模型便是基于Emory白质高信号数据集训练得到的。 ## 数据集组织 数据集按照固定的训练集与测试集进行组织，每个受试者对应一个独立目录： emory_wmh_dataset/├── README.md├── train/│ └── sub-XXXXXXXX/│ ├── original/│ ├── preprocessed/│ └── wmh.nii.gz├── test/│ └── sub-XXXXXXXX/│ ├── original/│ ├── preprocessed/│ └── wmh.nii.gz└── participants.tsv 每个受试者均被分配一个匿名标识符（sub-XXXXXXXX）。 ## 成像数据与标注 针对每位受试者，数据集包含以下内容： ### 预处理图像 1. 经N4偏置场校正的去面部标识FLAIR图像 2. 配准至FLAIR空间的经N4偏置场校正的去面部标识T1加权图像 ### 原始图像 1. 原始采集空间下的去面部标识FLAIR及T1加权图像 2. T1加权图像的去面部标识掩码 3. 将原始T1加权空间映射至FLAIR空间的仿射变换矩阵（FSL FLIRT格式） ### WMH标注 二值WMH分割掩码，与预处理后FLAIR空间对齐（0代表背景，1代表WMH） ## 元数据 受试者及扫描仪层面的元数据存储于participants.tsv文件中，可包括： 1. 人口统计学与临床变量（如年龄、性别、诊断、病因、认知评分） 2. 脑脊液生物标志物（如可获取） 3. 扫描仪信息，包括匿名化的扫描仪标识符与磁场强度 4. 数据集划分标识（训练集或测试集） 这些元数据支持针对人口统计学、临床及采集相关因素的分层分析。 ## 隐私与数据保护 所有图像均已进行去面部标识处理以移除面部特征。扫描仪标识符通过加盐单向加密变换进行匿名化，既可以防止身份重识别，又能保留扫描仪层面的分析可用性。
