Correction of MR k-space data corrupted by spike noise

Magnetic resonance images are reconstructed from digitized raw data, which are collected in the spatial-frequency domain (also called k-space). Occasi onally, single or multiple data points in the k-space data are corrupted by spike noise, causing striation artifacts in images. Thresholding methods f or detecting corrupted data points can fail because of small alterations, e specially for data points in the low spatial frequency area where the k-spa ce variation is large. Restoration of corrupted data points using interpola tions of neighboring pixels can give incorrect results. We propose a Fourie r transform method for detecting and restoring corrupted data points using a window filter derived from the striation-artifact structure in an image o r an intermediate domain. The method provides an analytical solution for th e alteration at each corrupted data point. It can effectively restore corru pted L-space data, removing striation artifacts in images, provided that th e following three conditions are satisfied. First, a region of known signal distribution (for example, air background) is visible in either the image or the intermediate domain so that it can be selected using a window filter . Second, multiple spikes are separated by the full-width at half-maximum o f the point spread function for the window filter. Third, the magnitude of a spike is larger than the minimum detectable value determined by the windo w filter and the standard deviation of k-space random noise.