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Abstract #2972

Intracranial vessel wall segmentation on 3D black-blood MRI using convolutional neural network

Hao Liu1, Dongye Li1,2, Xuesong Li3, Qiang Zhang1, Guanhua Wang1, Yishi Wang1, Xihai Zhao1, and Huijun Chen1

1Center for Biomedical Imaging Research, Tsinghua university, Beijing, China, 2Center for Brain Disorders Research, Capital Medical University, Beijing, China, 3School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

Intracranial artery atherosclerosis is a major cause of stroke. manually segmenting intracranial artery vessel wall is laborious and time-consuming. we proposed an automatic intracranial artery vessel wall segmentation framework to find the centerline of the intracranial artery from SNAP images to segment the final lumen and outer-wall contours on the cross-sectional 2D slices perpendicular to the centerline.

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