DocumentCode :
1392519
Title :
Correction of MR k-space data corrupted by spike noise
Author :
Kao, Yi-Hsuan ; MacFall, James R.
Author_Institution :
Inst. of Radiol. Sci., Nat. Yang-Ming Univ., Pei-Tou, Taiwan
Volume :
19
Issue :
7
fYear :
2000
fDate :
7/1/2000 12:00:00 AM
Firstpage :
671
Lastpage :
680
Abstract :
Magnetic resonance images are reconstructed from digitized raw data, which are collected in the spatial-frequency domain (also called k-space). Occasionally, single or multiple data points in the k-space data are corrupted by spike noise, causing striation artifacts in images. Thresholding methods for detecting corrupted data points can fail because of small alterations, especially for data points in the low spatial frequency area where the k-space variation is large. Restoration of corrupted data points using interpolations of neighboring pixels can give incorrect results. The authors propose a Fourier transform method for detecting and restoring corrupted data points using a window filter derived from the striation-artifact structure in an image or an intermediate domain. The method provides an analytical solution for the alteration at each corrupted data point. It can effectively restore corrupted k-space data, removing striation artifacts in images, provided that the following 3 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 of the point spread function for the window filter. Third, the magnitude of a spike is larger than the minimum detectable value determined by the window filter and the standard deviation of k-space random noise.
Keywords :
biomedical MRI; discrete Fourier transforms; frequency-domain analysis; image restoration; medical image processing; noise; MR k-space data; analytical solution; digitized raw data; full-width at half-maximum; intermediate domain; k-space random noise; magnetic resonance images reconstruction; medical diagnostic imaging; neighboring pixels interpolations; point spread function; spatial-frequency domain; spike magnitude; spike noise corrupted data; striation-artifact structure; window filter; Coils; Filters; Fourier transforms; Frequency domain analysis; Hardware; Image reconstruction; Image restoration; Interpolation; Magnetic resonance imaging; Magnetic separation; Artifacts; Brain; Fourier Analysis; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/42.875184
Filename :
875184
Link To Document :
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