Quantitative Assessment of Single-Image Super-Resolution in Myocardial Scar Imaging

Single-image super resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based image acquisition technique, such as MRI, remains unknown. We performed high-resolution ex vivo late gadolinium enhancement (LGE) magnetic resonance imaging (0.4
$\,\times\,$
0.4
$\,\times\,$
0.4
${\rm mm}^{{3}}$
) in postinfarction swine hearts
$(n=24)$
. The swine hearts were divided into the training set
$(n=14)$
and the test set
$(n=10)$
, and in all hearts, low-resolution images were simulated from the high-resolution images. In the training set, super-resolution dictionaries with pairs of small matching patches of the high- and low-resolution images were created. In the test set, super resolution recovered high-resolution images from low-resolution images using the dictionaries. The same algorithm was also applied to patient LGE
$(n=4)$
to assess its effects. Compared with interpolated images, super resolution significantly improved basic image quality indices
$(P<0.001)$
. Super resolution using Fourier-based zero padding achieved the best image quality. However, the magnitude of improvement was small in images with zero padding. Super resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. In conclusion, single-image super resolution significantly improves image errors. However, the magnitude of improvement was relatively small in images with Fourier-based zero padding. These findings provide evidence to support its potential use in myocardial scar imaging.