Level-Set Segmentation of Arterial and Venous Vessels based on ToF-SWI data

INTRODUCTION Non-invasive quantitative assessment of the cerebral vasculature is of high diagnostic and therapeutic interest. Prerequisite for quantitative description of blood vessels is voxel-wise classification of angiographic data sets into vessel and non-vessel structures. Among the vast of algorithms suitable for vessel segmentation [1, 2] the level-set technique has been established as a flexible segmentation approach that handles morphological variations [3]. The level-set method enables iterative evolution of an initial curve towards boundaries of target objects driven by combining internal (geometry of evolving curve) and external forces (produced by the data). In this contribution, we use a hybrid level-set approach [4] that relies on both boundary and region information to create a 3D representation of the arterial and venous vasculature.