Deep learning Based Automatic Segmentation of Brain Magnetic Resonance angiography Images

Accurate cerebrovascular segmentation plays an important role in clinical diagnosis and the related research. Magnetic Resonance angiography (MRA) postprocessing manually recognized by technologists is extremely labor intensive and error prone. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. We propose an artificial intelligence brain vessel segmentation system supported by an optimized physiological anatomical-based 3D convolutional neural network that can automatically achieve brain MRA vessel segmentaion in healthcare services. The overall segmentation accuracy of the independent testing dataset is 0.931.