The Multi-Class Segmentation of the Human Cerebral Vasculature in TOF-MRA: A Supervised Deep Learning Approach

Currently, there is no accurate fully automated multi-class method to segment the whole cerebral arterial tree in time-of-flight magnetic resonance angiography (TOF-MRA). We developed an artificial intelligence based software tool to identify cerebral arteries in TOF-MRAs. We trained a neural network on a TOF-MRA dataset and labeled the cerebral arterial tree using different image processing techniques. Our software tool is fast and reliable, with no human intervention, and allows for the conduction of large-scale TOF-MRA studies while being versatile in segmenting a diverse set of TOF-MRAs.