Keywords: Whole Joint, Bone, deep learning; knee joint; image quality; meniscus injury; MRI
Motivation: The need for accurate meniscus injury diagnosis and the limitations of traditional MRI.
Goal(s): To enhance knee MRI through deep learning algorithms.
Approach: A cohort of 46 patients underwent MRI with and without deep learning reconstruction (DLR). Radiologists subjectively assessed image quality and evaluated meniscus damage.
Results: DLR improved image quality, reducing noise and artifacts. Radiologists consistently rated DLR images higher. DLR excelled in detecting subtle meniscus injuries compared to traditional MRI.
Impact: This study demonstrates that deep learning-based MRI reconstruction substantially improves image quality and the detection of subtle meniscus injuries, offering enhanced diagnostic accuracy in knee joint assessments.
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