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Abstract #3364

Reconstruction of synthetic T1 MPRAGE via Deep Neural Network from Multi Echo Gradient Echo images.

Kanghyun Ryu1, Yoonho Nam2, Na-young Shin2, Jinhee Jang2, Jiyong Park1, 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

We propose to use deep learning to reconstruct synthetic T1-weighted Magnetization prepared rapid gradient echo (MPRAGE) image from multi echo gradient echo (mGRE) images. With our method, high tissue contrast can be achieved without actual MPRAGE scan, which could be utilized for post processing methods, such as tissue segmentation or volumetric quantification. We validated our method’s accuracy by comparing the result of synthetic images with the true image via segmentation and volumetry. Additionally, we tested our method on clinical images containing pathologies not seen in the training set.

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