POLAR SAMPLING IN K-SPACE - RECONSTRUCTION EFFECTS

Magnetic resonance images are most commonly computed by taking the inv erse Fourier transform of the k-space data. This transformation can po tentially create artifacts in the image, depending on the reconstructi on algorithm used. For equally spaced radial and azimuthal k-space pol ar sampling, both gridding and convolution backprojection are applicab le. However, these algorithms potentially can yield different resoluti on, signal-to-noise ratio, and aliasing characteristics in the reconst ructed image. Here, these effects are analyzed and their tradeoffs are discussed. It is shown that, provided the modulation transfer functio n and the signal-to-noise ratio are considered together, these algorit hms perform similarly. In contrast, their aliasing behavior is differe nt, since their respective point spread functions (PSF) differ. in gri dding, the PSF is composed of the mainlobe and ringlobes that lead to aliasing. Conversely, there are no ringlobes in the convolution backpr ojection PSF, thus radial aliasing effects are minimized. Also, a hybr id gridding and convolution backprojection reconstruction is presented for radially nonequidistant k-space polar sampling.