Abstract #2972

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

Hao Liu¹, Dongye Li^1,2, 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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