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Abstract #1759

DeepSlider: Deep learning-powered gSlider for improved robustness and performance

Juhyung Park1, Dongmyung Shin1, Hyeong-Geol Shin1, Jiye Kim1, and Jongho Lee1
1Seoul National University, Seoul, Korea, Republic of

We designed a slab-encoding RF pulse set, referred to as DeepSlider, using deep reinforcement learning to improve the robustness and performance. The condition number of the RF encoding matrix, which determines the sensitivity of the design to noise, was optimized via deep reinforcement learning and gradient descent. Additionally, the design was extended from reconstructing the real signal to the complex signal, allowing us to utilize the complex signal instead of the real part, expanding the application of the pulse to phase-based imaging.

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