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Abstract #2223

Transfer Learning for Compressed-sensing Cardiac CINE MRI

Seong-Jae Park1, Jong-Hyun Yoon2, and Chang-Beom Ahn1
1Kwangwoon University, Seoul, Republic of Korea, 2Gachon University, Incheon, Republic of Korea

Compressed-sensing cardiovascular CINE MRI was performed using deep artificial neural network and transfer learning. Transfer learning is a method to use weights obtained from previous learning as initial weights for current learning to improve generality and performance of the neural network. When learning data is limited, it is useful for generalization by using previous learning along with other data. It also reduces learning time by 80 to 98 percent. And to prevent modification of measurement data by Deep learning, K-space correction was added as a post-processing process.

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