Purpose: to propose a two-step non-local principal component analysis (PCA) method and demonstrate its utility for denoising diffusion tensor MRI (DTI) with a few diffusion directions.
Methods: A two-step denoising pipeline was implemented to ensure accurate patch selection even with high noise levels and was coupled with data preprocessing for g-factor normalization and phase stabilization before data denoising with a non-local PCA algorithm. At the heart of our proposed pipeline was the use of a data-driven optimal shrinkage algorithm to manipulate the singular values in a way that would optimally estimate the noise-free signal.
Purpose: To develop and characterize the performance of a 128-channel head array for brain imaging at 10.5 tesla and evaluate the potential of brain imaging at this unique, >10 tesla magnetic field.
Methods: The coil is composed of a 16-channel self-decoupled loop transmit/receive array with a 112-loop receive-only (Rx) insert.
Purpose: To propose a novel method for parallel-transmission (pTx) spatial-spectral pulse design and demonstrate its utility for robust uniform water-selective excitation (water excitation) across the entire brain.
Theory And Methods: Our design problem is formulated as a magnitude-least-squares minimization with joint RF and k-space optimization under explicit specific-absorption-rate constraints. For improved robustness against off-resonance effects, the spectral component of the excitation target is prescribed to have a water passband and a fat stopband.