摘要：We systematically evaluated a variety of MR spiral imaging acquisition and
reconstruction schemes using a computational perceptual difference model (PDM)
that models the ability of humans to perceive a visual difference between a degraded
“fast” MRI image with subsampling of k-space and a “gold standard” image mimicking full acquisition. Human subject experiments performed using a modified
double-stimulus continuous-quality scale (DSCQS) correlated well with PDM, over a
variety of images. In a smaller set of conditions, PDM scores agreed very well with
human detectability measurements of image quality. Having validated the technique,
PDM was used to systematically evaluate 2016 spiral image conditions (six interleave
patterns, seven sampling densities, three density compensation schemes, four
reconstruction methods, and four noise levels). Voronoi (VOR) with conventional
regridding gave the best reconstructions. At a fixed sampling density, more
interleaves gave better results. With noise present more interleaves and samples were
desirable. With PDM, conditions were determined where equivalent image quality
was obtained with 50% sampling in noise-free conditions. We conclude that PDM
scoring provides an objective, useful tool for the assessment of fast MR image quality
that can greatly aid the design of MR acquisition and signal processing strategies.
