An unbiased signal-to-noise ratio measure for magnetic resonance images.

Estimating the true signal-to-noise ratio (SNR) of magnetic resonance (MR) images with low signal is confounded by the magnitude presentation of the data. This paper suggests a simple solution to this problem. A common method of measuring SNR compares the mean signal to the standard deviation of the noise.

Quantitative evaluation of several partial Fourier reconstruction algorithms used in MRI.

Partial Fourier reconstruction algorithms exploit the redundancy in magnetic resonance data sets so that half of the data is calculated during image reconstruction rather than acquired. The conjugate synthesis, Margosian, homodyne detection, Cuppen and POCS algorithms are evaluated using spatial frequency domain analysis to show their characteristics and where limitations may occur. The phase correction used in partial Fourier reconstruction is equivalent to a convolution in the frequency domain and the importance of accurately implementing this convolution is demonstrated.