Accurate and fast automatic Carotid artery segmentation of time of flight(TOF) MRA plays an important role in the auxiliary diagnosis of carotid artery disease. Considering the complexity and uncertainty of doctors’ manual segmentation of neck vessels, automatic segmentation algorithms are required in clinical practice. A segmentation model based on 3D Convolutional neural network (CNN) was proposed to segment carotid arteries from TOF MRA images. With innovative adjustment of the network architecture and parameters for carotid application, our model showed better performance than other baseline models on private dataset.
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