23Na MRI provides important information for many pathologies. However, its low SNR entails low spatial resolutions and long acquisition times. The proposed work reconstructs 3D radially undersampled in vivo 30-channel 23Na head data at B0=7T with a sensitivity encoding using a nonlinear conjugate gradient method (CG-SENSE) including a total variation and a discrete cosine transform. With CG-SENSE using iteratively generated Lagrangian coil sensitivities, image quality and contrast within the object are improved compared to sum of squares (SOS) and adaptive combination (ADC) reconstructions.
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