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Abstract #1290

Fiber orientation robust myelin water fraction mapping using complex-valued neural network in multi-echo gradient echo

Soozy Jung1, Kanghyun Ryu1, Jae Eun Song1, Mina Park2, and Dong-Hyun Kim1
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of, 2Department of Radiology, Gangnam Severance Hospital, Seoul, Korea, Republic of

Recently, magnitude-based artificial neural network (ANN) method was implemented to estimate myelin water fraction (MWF) mapping using multi-echo gradient-echo (mGRE) data. However, MWF mapping in mGRE data requires phase information with the demand of considering frequency shifts in white matter. Here, we developed a complex-valued ANN for MWF mapping which could learn the phase information of the mGRE signal. According to simulation and in vivo analysis, complex-valued ANN is more robust to fiber orientation and noise than magnitude-based ANN and conventional fitting method.

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