Enhancing MRI Image Quality and Meniscus Injury grading in Knee Joints with Deep Learning

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.