Generalisability of Image Quality Transfer: Can we approximate in-vivo human brains from dead monkey brains?

The Image-Quality Transfer (IQT) framework enhances low quality images by transferring information from high quality images acquired on expensive bespoke scanners. Although IQT has major potential in medical imaging, one key question is its dependence on training data. We demonstrate the generalisability of IQT used for super-resolution by showing that reconstruction of in-vivo human images degrades minimally from training on human data from the same study, to data from a different demographic and imaging protocol, to data from fixed monkey brains. Remarkably, a patchwork of fixed monkey brain image-pieces is hardly distinguishable from a reconstruction using pieces of human data.