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Abstract #2962

Improving Fast 3D-T1rho Mapping of Human Knee Cartilage with Data-Driven Learned Sampling Pattern

Marcelo Victor Wust Zibetti1, Azadeh Sharafi1, and Ravinder Regatte1
1Radiology, NYU Langone Health, New York, NY, United States

in evaluating the performance of optimized SP for accelerating T1rho mapping of the knee cartilage. In this study, we investigate the improvements in accelerating the T1rho mapping of knee joint by learning the SP in a data-driven manner. It was observed that the optimal learned SP depends on the selected spatial-temporal (k-t) data and the chosen reconstruction. Our preliminary results show that the learned SP improved the quality of the accelerated T1rho mapping of knee cartilage over Poisson disk for several different kinds of CS reconstructions.

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