Improving Quantitative Magnetic Resonance Imaging Using Deep Learning

Semin Musculoskelet Radiol 2020; 24: 451-459 DOI: 10.1055/s-0040-1709482Deep learning methods have shown promising results for accelerating quantitative musculoskeletal (MSK) magnetic resonance imaging (MRI) for T2 and T1ρ relaxometry. These methods have been shown to improve musculoskeletal tissue segmentation on parametric maps, allowing efficient and accurate T2 and T1ρ relaxometry analysis for monitoring and predicting MSK diseases. Deep learning methods have shown promising results for disease detection on quantitative MRI with diagnostic performance superior to conventional machine-learning methods for identifying knee osteoarthritis. [...] Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.Article in Thieme eJournals: Table of contents  |  Abstract  |  Full text
Source: Seminars in Musculoskeletal Radiology - Category: Radiology Authors: Tags: Review Article Source Type: research