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Abstract #2863

Automated 3D modeling and analysis of cerebral small vessels with MR angiography at 7 Tesla

Zhixin Li1,2,3, Yue Wu1,2,3, Dongbiao Sun1,2,3, Jing An4, Qingle Kong5, Rong Xue1,2,3, Yan Zhuo1,2,3, and Zihao Zhang1,2,3
1State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, 2The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China, 3University of Chinese Academy of Sciences, Beijing, China, 4Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, 5MR Collaboration, Siemens Healthcare Ltd, Beijing, China

Due to the possible interaction between cerebral small vessel disease (CSVD) and a variety of brain diseases or pathological changes, people's interest in small vessel pathology was growing. With the increased imaging resolution at ultra-high field MRI, imaging cerebral small vessels become feasible with TOF-MRA sequence. In this study, we introduced an automated vascular segmentation and tracing method based on deep learning, machine learning and multi filtering. Our method performed well for the multistage branching of cerebral vessels, and could quantitatively evaluate the vasculature. The technique was potentially useful for the clinical studies of CSVD.

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