Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial Intelligence
This study aims to shorten the diffusion spectral imaging (DSI) scan time to a clinically acceptable level while providing satisfactory complex white matter fiber structure description as well as accurate diffusion metric quantification by applying deep learning-based reconstruction. Images were acquired using conventional (≈30 min) and rapid (≈8 min) DSI sequences, and reconstructed using conventional and DL-based methods, respectively. Atlas-based fiber-tracking and diffusion metrics quantification from various advanced models were conducted. The results demonstrated that the 8-minute rapid DSI sequence combined with DL-recon can provide complex fiber structure tractography and advanced diffusion metric quantification of satisfactory quality.
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