Abstract Objectives The aim of this study was to evaluate the image quality and diagnostic performance of a deep-learning (DL)–accelerated two–dimensional (2D) turbo spin echo (TSE) MRI of the knee at 1.5 and 3 T in clinical routine in comparison to standard MRI. Material and methods Sixty participants, who underwent knee MRI at 1.5 and 3 T between October/2020 and March/2021 with a protocol using standard 2D–TSE (TSE_S) and DL–accelerated 2D–TSE sequences (TSE_DL), were enrolled in this prospective institutional review board–approved study. Three radiologists assessed the sequences regarding structural abnormalities and evaluated the images concerning overall image quality, artifacts, noise, sharpness, subjective signal-to-noise ratio, and diagnostic confidence using a Likert scale (1–5, 5 = best). Results Overall image quality for TSE_DL was rated to be excellent (median 5, IQR 4–5), significantly higher compared to TSE_S (median 5, IQR 4 – 5, p < 0.05), showing significantly lower extents of noise and improved sharpness (p < 0.001). Inter- and intra-reader agreement was almost perfect (κ = 0.92–1.00) for the detection of internal derangement and substantial to almost perfect (κ = 0.58–0.98) for the assessment of cartilage defects. No difference was found concerning the detection of bone marrow edema and fractures. The diagnostic confidence of TSE_DL was rated to be comparable to that of TSE_S (median 5, IQR 5–5, p > 0.05). Time of acquisition could be reduced to 6:11 min using TSE_DL compared to 11:56 min for a protocol using TSE_S. Conclusion TSE_DL of the knee is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared to TSE_S, reducing the acquisition time about 50%. Key Points • Deep-learning reconstructed TSE imaging is able to almost halve the acquisition time of a three-plane knee MRI with proton density and T1-weighted images, from 11:56 min to 6:11 min at 3 T. • Deep-learning reconstructed TSE imaging of the knee provided significant improvement of noise levels (p < 0.001), providing higher image quality (p < 0.05) compared to conventional TSE imaging. • Deep-learning reconstructed TSE imaging of the knee had similar diagnostic performance for internal derangement of the knee compared to standard TSE.