Keywords: Machine Learning/Artificial Intelligence, MSKCombining parallel imaging (PI) and simultaneous multislice (SMS) acceleration realized a clinical 4-fold accelerated 2D TSE MRI of the knee. However, 8-fold acceleration with conventional reconstruction methods suffers from significant image quality degradation. We propose a complete DL approach for combined slice separation and k-space-to-image reconstruction of SMS-PI-accelerated knee MRI with tunable denoising strength and super-resolution image enhancement. The proposed methods enable artifact-free image reconstruction of 8-fold accelerated 2D TSE MR images in multiple planes and with multiple image contrasts. Clinical evaluations suggest equivalence of image quality and detection rates of 8-fold S2P4 DL reconstructions compared to the reference standard.
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