Keywords: Machine Learning/Artificial Intelligence, AI/ML Image Reconstruction, 3D MSK, Segmentation, Cartilage, Meniscus
Motivation: Current 2D knee MRI requires multiple scans, while 3D FSE (CUBE) offers single-scan advantages but faces blurring and low SNR. Emerging DL methods may enhance image quality and speed.
Goal(s): To evaluate a novel DL-based acquisition and reconstruction method (Sonic DL) for 3D CUBE to reduce scan time while enabling accurate cartilage and meniscus morphometry.
Approach: 14 patients were imaged with 2D FSE, DL CUBE and Sonic DL CUBE. Segmentation, thickness mapping and diagnostic confidence were assessed.
Results: Sonic DL CUBE reduced scan time by 40%, providing reliable morphometry with lesion conspicuity similar or superior to routine 2D FSE.
Impact: Sonic DL technique enables 10-fold acceleration of 3D FSE, delivering accurate cartilage and meniscus morphometry. Its superior sharpness and lesion conspicuity offer potential for routine clinical use, improving both diagnostic confidence in 3D knee imaging and patient throughput.
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