Abstract #2660

Reduction of respiratory motion artifact in c-spine imaging using deep learning: Is substitution of navigator possible?

Hongpyo Lee¹, Kanghyun Ryu¹, Yoonho Nam², Jaeho Lee¹, and Dong-Hyun Kim¹

¹Yonsei University, Seoul, Republic of Korea, ²Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

Deep learning methods are starting to be widely used in medical images. Here, we propose a deep learning approach to compensate respiratory induced artifacts. A deep convolutional neural network was designed to train the ghosting artifact caused by respiratory motion in c-spine imaging. Using deep learning, compensation can be applied without additional data such as navigator echo.

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