  We present a novel method that allows for measuring the quality of
diffusion-weighted MR images dependent on the image resolution and the image
noise. For this purpose, we introduce a new thresholding technique so that
noise and the signal can automatically be estimated from a single data set.
Thus, no user interaction as well as no double acquisition technique, which
requires a time-consuming proper geometrical registration, is needed. As a
coarser image resolution or slice thickness leads to a higher signal-to-noise
ratio (SNR), our benchmark determines a resolution-independent quality measure
so that images with different resolutions can be adequately compared. To
evaluate our method, a set of diffusion-weighted images from different vendors
is used. It is shown that the quality can efficiently be determined and that
the automatically computed SNR is comparable to the SNR which is measured
manually in a manually selected region of interest.
