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Abstract #3022

3D T2-FFE MR Neurography of lumbosacral plexus with a deep learning constrained Compressed SENSE reconstruction

Caijuan Zhang1, Dong Dong1, Shiyu Guo1, Lishan Wu1, Yi Zhu2, Ke Jiang2, and Wenxin Wang2
1Radiology, First Hospital of Jilin University, changchun, China, 2Philips Heathcare, Beijing, China

Synopsis

Three-dimensional (3D) T2 Fast Field Echo (FFE) sequence of MR Neurography always takes a very long scan time. However, using very high acceleration factors (AF) will result in degradation of image quality due to insufficient noise removal. In this study, we used Compressed-SENSE Artificial Intelligence (CS-AI) framework to acquire highly accelerated T2 FFE imaging in lumbosacral plexus. The results showed that CS-AI reconstruction might significantly decrease scan time with sufficient image quality compared with conventional SENSE, and might be clinically useful for assessment of lumbosacral plexus.

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