Mass spectrometry imaging (MSI) allows us to visualize the spatial distribution of molecular
components in a sample. A large amount of mass spectrometry data comprehensively provides molecular distributions. In this study, we focus on the information in the obtained data
and use the Shannon entropy as a quantity to analyze MSI data. By calculating the Shannon
entropy at each pixel on a sample, the spatial distribution of the Shannon entropy is obtained
from MSI data. We found that low-entropy pixels in entropy heat maps for kidneys of mice
had different structures between two ages (3 months and 31 months). Such changes cannot
be visualized by conventional imaging techniques. We further propose a method to find
informative molecules. As a demonstration of the proposed scheme, we identified two molecules by setting a region of interest which contained low-entropy pixels and by exploring
changes of peaks in the region.