Aneumo: A Large-Scale Comprehensive Synthetic Dataset of Aneurysm Hemodynamics
Journal:
arXiv
Published Date:
Jan 17, 2025
Abstract
Intracranial aneurysm (IA) is a common cerebrovascular disease that is
usually asymptomatic but may cause severe subarachnoid hemorrhage (SAH) if
ruptured. Although clinical practice is usually based on individual factors and
morphological features of the aneurysm, its pathophysiology and hemodynamic
mechanisms remain controversial. To address the limitations of current
research, this study constructed a comprehensive hemodynamic dataset of
intracranial aneurysms. The dataset is based on 466 real aneurysm models, and
10,000 synthetic models were generated by resection and deformation operations,
including 466 aneurysm-free models and 9,534 deformed aneurysm models. The
dataset also provides medical image-like segmentation mask files to support
insightful analysis. In addition, the dataset contains hemodynamic data
measured at eight steady-state flow rates (0.001 to 0.004 kg/s), including
critical parameters such as flow velocity, pressure, and wall shear stress,
providing a valuable resource for investigating aneurysm pathogenesis and
clinical prediction. This dataset will help advance the understanding of the
pathologic features and hemodynamic mechanisms of intracranial aneurysms and
support in-depth research in related fields. Dataset hosted at
https://github.com/Xigui-Li/Aneumo.
