Feng Yanqiu

Improved Algorithm for Motion Estimation in the Reconstruction of PROPELLER MRI Data

Algorithms to reliably and accurately extract inter-strip motion are crucial for motion artifacts suppression in PROPELLER MRI. The current algorithm is based on image registration through maximizing correlation coefficients of k-space data. To decouple rotational and translational estimation, only magnitude of k-space data is taken into account while performing rotational estimation. Because little data are contained in the central overlapped sampling area, the robustness and precision of the k-space based rotational estimation are degraded by the discarding of useful phase information. In this paper, an improved algorithm through optimizing correlation in image space is proposed. First, k-space data are transformed into image space by zero-padded reconstruction of each strip. Then the rotational and translational parameters are acquired simultaneously through maximizing correlation coefficients between these images with POWELL optimization. Phantom and in vivo imaging demonstrate that the proposed image-space-based algorithm is of a much higher accuracy than the k-space-based algorithm.

Improved Reconstruction of Parallel MR Data Using Smoothing Constraints

MR data acquisition efficiency can be greatly improved by the spatial sensitivity encoding using multiple coils in parallel MR imaging. However, when large reduce factor are chosen, scanning noise may be amplified and leads to serious artifacts in the image, due to the ill-conditioning in matrix inversion in the reconstruction. In this paper, a new framework, which can incorporate advanced edge-preserving smoothing techniques, is proposed for the regularized reconstruction of parallel MR data. Under the proposed framework, algorithm with smoothing constraints based on non-local means, which has the advantage of preserving the small structures well while filtering out noise, is presented for parallel imaging. Experiment on in-vivo brain imaging using the array of 8 coils shows that the noise and artifacts in the final reconstruction with large reduction factor can be better suppressed with the proposed algorithm.