Rationale: Mass Spectrometry Imaging (MSI) is useful for analyzing biological samples directly, as a spatially resolved, label-free technique. Here we present a method for super-resolution reconstruction of sparse representation to improve resolution of MSI data.
Methods: Air Flow-Assisted Ionization Mass Spectrometry Imaging (AFAI-MSI) was used to acquire MSI data from ink samples, thyroid tumour samples, rat renal biopsies, and rat brain biopsy samples. Super-resolution reconstruction of sparse representation was adopted for the collected MSI data.
Results: After comparison of the reconstructed high-resolution image and the original high-resolution image, it is found that super-resolution reconstruction image is closer to the original high-resolution image than the image obtained with the interpolation method, and the highest Peak Signal-to-Noise Ratio (PSNR) difference value is over 1.4dB. Therefore, the application of the super-resolution reconstruction technique, based on sparse representation MSI, is feasible and effective.
Conclusions: The method proposed here not only improves the resolution of MSI in post-data processing, but also acquires fewer sampling points at the same resolution, thereby greatly reducing the sampling time, with great application value for large-volume sample MSI, high-resolution MSI, etc.
Copyright © 2015 John Wiley & Sons, Ltd.