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Abstract #1305

Deep Learning Segmentation of Lenticulostriate Arteries on 3D Black Blood MRI

Samantha J Ma1, Mona Sharifi Sarabi1, Kai Wang1, Soroush Heidari Pahlavian1, Wenli Tan1, Madison Lodge1, Lirong Yan1, Yonggang Shi1, and Danny JJ Wang1
1University of Southern California, Los Angeles, CA, United States

Cerebral small vessels are largely inaccessible to existing clinical in vivo imaging technologies. As such, early cerebral microvascular morphological changes in small vessel disease (SVD) are difficult to evaluate. A deep learning (DL)-based algorithm was developed to automatically segment lenticulostriate arteries (LSAs) in 3D black blood images acquired at 3T. Using manual segmentations as supervision, 3D segmentation of LSAs is demonstrated to be feasible with relatively high performance and can serve as a useful tool for quantitative morphometric analysis in patients with cerebral SVD.

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