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Abstract #2806

Deep-learned STIR imaging via Deep Learning with multi-contrast MRI

Hanbyol Jang1,2, Jinseong Jang1, Kihun Bang1,2, and Dosik Hwang1

1Yonsei University, Seoul, Republic of Korea, 2Philips Korea, Seoul, Republic of Korea

The goal of this study is to make STIR MRI using deep learning with multi-contrast MRI. First, we simulated the phantom image created by the bloch equation, which is the basic formula for making MRI, and confirmed that the convolution neural network learns the bloch equation. We also showed the feasibility of making STIR image with in-vivo T1- and T2-weighted, and GRE images in the knee.

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