Synthetic Vessels 0.1

This dataset consists of a set of synthetically generated 3D vessels, intended to support the development and benchmarking of representation learning models for continuous 3D vascular geometry, particularly for models capable of capturing fine-grain details like stenoses. The generation framework is based on physical principles designed to produce a wide variety of smooth, biologically-inspired vessel structures. Each vessel is represented as a generalized cylinder, stored as an array of shape (n, 4), where n is the number of points along the curvilinear centerline. The four coordinates represent the x, y, z position and the vessel radius (r) at that point. The 3D curvilinear centerlines are created by numerically integrating the trajectory of a particle under a set of dynamic forces. This produces a wide variety of smooth, tapering vessel paths. A radius profile is generated along the arc of each vessel. Simulated narrowings (localised stenoses) are added to 50% of the generated vessels. These stenoses are characterised by their position, size, and severity (occlusion), which are introduced by modifying the radius profile with a smooth bump function. More information, can be found in the associated GitHub repository: https://github.com/JamesBatten/SyntheticVessels本数据集包含一批合成生成的三维血管模型，旨在支撑面向连续三维血管几何的表征学习模型（representation learning models）的开发与基准测试，尤其针对可捕捉狭窄（stenoses）这类细粒度细节的模型。 该数据集的生成框架基于物理原理，旨在生成多样化的、符合生物学特征的光滑血管结构。每条血管被表示为广义圆柱（generalized cylinder），以形状为(n, 4)的数组存储：其中n为沿曲线中心线的采样点数，四个坐标分别对应该点的x、y、z空间位置与血管半径(r)。 三维曲线中心线通过对一组动态力作用下的粒子轨迹进行数值积分生成，由此可得到多样化的光滑渐缩血管路径。沿每条血管的弧长生成半径分布。在50%的生成血管中添加模拟的局部狭窄（localised stenoses）病灶：这类狭窄以位置、尺寸与闭塞程度（occlusion）为特征，通过平滑bump函数修改半径分布实现。 更多详细信息可查阅关联的GitHub仓库：https://github.com/JamesBatten/SyntheticVessels