Lausanne_TOF-MRA_Aneurysm_Cohort
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This dataset was obtained from the Lausanne University Hospital (CHUV). Accession #: ds-aneurysms-lausanne Description: This dataset set is composed of 284 TOF-MRA subjects, of which 127 are healthy controls and 157 are patients with brain aneurysm(s). Please cite the following reference if you use this dataset: Di Noto, et al. "Towards Automated Brain Aneurysm Detection in TOF-MRA: Open Data, Weak Labels, and Anatomical Knowledge", Neuroinformatics, 2022, https://doi.org/10.1007/s12021-022-09597-0 Here is an overview of the dataset organization: every original folder (i.e. non-derivative) contains the TOF-MRA and the T1w volume of the subjects. Instead, the "derivatives" folder contains 3 sub-folders: 1) "manual_masks": for controls, it only contains the skull-stripped TOF-MRA volume; for patients, it contains the skull-stripped volume and the binary manual mask(s) of the aneurysm(s). 2) "N4_bias_field_corrected": for every subject, it contains the N4-bias-field-corrected TOF-MRA volume and the corresponding N4-bias-field-corrected skull-stripped volume. 3) "registrations": it contains 3 sub-folders 3.1) "reg_metrics": for every subject/session, it contains the registration quality metrics. We performed 2 registrations: MNI_2_T1w, and T1w_2_TOF. For each of these registrations, we save the ANTsNeighborhoodCorrelation and MattesMutualInformation of the ANTs package. The metrics can be used to check which are the subjects for which the registration was not accurate. 3.2) "reg_params": for every subject/session, it contains the parameters used in the registration (i.e., warp fields and .mat files). 3.3) "vesselMNI_2_angioTOF": for every subject/session, it contains the probabilistic vessel atlas (Mouches et al., 2019) co-registered to TOF-MRA subject space.
本数据集取自瑞士洛桑大学附属医院（CHUV）。 登录号：ds-aneurysms-lausanne 数据集描述：本数据集包含284例时间飞越法磁共振血管造影（TOF-MRA）受试者，其中127名为健康对照者，157名为脑动脉瘤患者。 若使用本数据集，请引用以下文献： Di Noto 等人. "Towards Automated Brain Aneurysm Detection in TOF-MRA: Open Data, Weak Labels, and Anatomical Knowledge", *Neuroinformatics*, 2022, https://doi.org/10.1007/s12021-022-09597-0 以下为数据集组织概览：所有原始文件夹（即非衍生类文件夹）均包含受试者的TOF-MRA及T1加权成像（T1w）数据。而"derivatives（衍生数据）"文件夹包含3个子文件夹： 1) "manual_masks（手动掩码）"：对于健康对照者，仅包含剥离颅骨后的TOF-MRA体积数据；对于患者，则包含剥离颅骨后的体积数据及动脉瘤的二进制手动掩码。 2) "N4_bias_field_corrected（N4偏置场校正）"：针对所有受试者，均包含经过N4偏置场校正的TOF-MRA体积数据，以及对应的经N4偏置场校正的剥离颅骨体积数据。 3) "registrations（配准）"：该文件夹包含3个子文件夹： 3.1) "reg_metrics（配准质量指标）"：针对每位受试者/扫描时段，均包含配准质量指标。本研究共执行两次配准：MNI_2_T1w（蒙特利尔神经研究所空间配准至T1w空间）及T1w_2_TOF（T1w空间配准至TOF-MRA空间）。针对每一次配准，均保存ANTs软件包的邻域互相关（ANTsNeighborhoodCorrelation）与马特斯互信息（MattesMutualInformation）。此类指标可用于筛选配准效果不佳的受试者。 3.2) "reg_params（配准参数）"：针对每位受试者/扫描时段，均包含配准所用的参数（即形变场及.mat格式文件）。 3.3) "vesselMNI_2_angioTOF"：针对每位受试者/扫描时段，均包含共配准至TOF-MRA受试者空间的概率性血管图谱（Mouches等，2019）。
