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Abstract #1160

Accelerated 3D Myelin Water Imaging using Joint Parallel Imaging and Variable Splitting Network

Jae-Hun Lee1, Jaeuk Yi1, Kanghyun Ryu2, Soozy Jung1, and Dong-Hyun Kim1
1Department of Electrical & Electronic Engineering, Yonsei Univ., Seoul, Korea, Republic of, 2Department of Radiology, Stanford Univ., Stanford, CA, United States

Myelin water imaging using multi-cho GRE (mGRE) requires long acquisition times. In this study, we explored a multi-step reconstruction method using both advanced parallel imaging and deep learning, which can utilize joint information between the multi-echo images to further accelerate the acquisition. The proposed method shows acceptable image quality with improved quantitative values compared to conventional methods. The proposed method can achieve high acceleration factors for mGRE based 3D myelin water imaging.

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