Fast Regularized Reconstruction of Non-Uniformly Subsampled Partial-Fourier Parallel MRI Data

We present an adaptation of our previous fast, regularized parallel MRI reconstruction approach (LSQR-Hybrid) to encompass the reconstruction of partial-Fourier data. Reconstructions of partial-Fourier data require a constraint on the signal phase variation in the reconstructed image. Here, we employ a two-parameter Tikhonov regularization formulation to constrain the real and imaginary components separately. A variation of the LSQR-Hybrid algorithm is used to rapidly reconstruct a set of images across the two-dimensional regularization parameter search space. The “best” image available is chosen as the one with the least system error using the most regularization. Results are demonstrated with subsam

• Type: Conference
• Year: 2007
• Where: ISBI
• Authors: William Scott Hoge, Misha Elena Kilmer, Carlos Zacarias-Almarcha, Dana H. Brooks
• Keywords: ISBI 2007, Medical Imaging, Partial-Fourier Data, Tikhonov Regularization Formulation, Two-dimensional Regularization Parameter