Relation between one- and two-dimensional noise power spectra of magnetic resonance images.

Our purpose in this study was to elucidate the relation between the one-dimensional (1D) and two-dimensional (2D) noise power spectra (NPSs) in magnetic resonance imaging (MRI). We measured the 1D NPSs using the slit method and the radial frequency method. In the slit method, numerical slits 1 pixel wide and L pixels long were placed on a noise image (128 × 128 pixels) and scanned in the MR image domain. We obtained the 1D NPS using the slit method (1D NPS_Slit) and the 2D NPS of the noise region scanned by the slit (2D NPS_Slit). We also obtained 1D NPS using the radial frequency method (1D NPS_Radial) by averaging the NPS values on the circumference of a circle centered at the origin of the original 2D NPS. The properties of the 1D NPS_Slits varied with L and the scanning direction in PROPELLER MRI. The 2D NPS_Slit shapes matched that of the original 2D NPS, but were compressed by L/128. The central line profiles of the 2D NPS_Slits and the 1D NPS_Slits matched exactly. Therefore, the 1D NPS_Slits reflected not only the NPS values on the central axis of the original 2D NPS, but also the NPS values around the central axis. Moreover, the measurement precisions of the 1D NPS_Slits were lower than those of the 1D NPS_Radial. Consequently, it is necessary to select the approach applied for 1D NPS measurements according to the data acquisition method and the purpose of the noise evaluation.

[Evaluation of Vessel Depictability in Compressed Sensing MR Angiography Using Numerical Phantom Model].

As an acceleration technique for use with magnetic resonance imaging (MRI), compressed sensing MRI (CSMRI) was introduced recently to obtain MR images from under sampled k-space data. Images generated using a nonlinear iterative procedure based on sophisticated theory in informatics using data sparsity have complicated characteristics. Therefore, the factors affecting image quality (IQ) in CS-MRI must be elucidated. This article specifically describes the examination of the IQ of clinically important MR angiography (MRA). For MRA, the depictability of thin blood vessels is extremely important, but quantitative evaluation of thin blood vessel depictability is difficult. Therefore, we conducted numerical experiments using a simple numerical phantom model mimicking the cerebral arteries so that the experimental conditions, including the thin vessel positions, can be given. Results show that vessel depictability changed depending on the noise intensity when the wavelet transform was used as the sparsifying transform. Decreased vessel depictability might present difficulties at the clinical signal-to-noise ratio (SNR) level. Therefore, selecting data acquisition and reconstruction conditions carefully in terms of the SNR is crucially important for CS-MRI study.

Noise Power Spectrum in PROPELLER MR Imaging.

The noise power spectrum (NPS), an index for noise evaluation, represents the frequency characteristics of image noise. We measured the NPS in PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) magnetic resonance (MR) imaging, a nonuniform data sampling technique, as an initial study for practical MR image evaluation using the NPS. The 2-dimensional (2D) NPS reflected the k-space sampling density and showed agreement with the shape of the k-space trajectory as expected theoretically. Additionally, the 2D NPS allowed visualization of a part of the image reconstruction process, such as filtering and motion correction.