Nowadays, the preclinical imaging methods are the most effective tools to perform researches in the fields of medical and biological sciences and pharmaceutical developments. During my investigations I worked up medical images and data of positron emission tomography (PET) and magnetic resonance imaging (MRI) which were connected for genetically modified animals, so called transgenic mouse (APP/PS1). There were four groups of the animals which served for modeling the early type of the Alzheimer’s disease. Imaging methods were performed via special software which is provided for preclinical postprocessing. Using these processed images the 18F-fluorodeoxyglucose distribution in the brain were analyzed, especially focused on 12 brain segments. The region of interest (ROI) suiting was made by brain atlas segmentation. I determined the standardized uptake volume (SUV) for all regions and I used non-parametric Kruskal-Wallis test and Mann-Whitney-Wilcoxon test to compare the groups. I identified brain regions which were significantly differ from each other at 5% significance level. The parts of the brain are consequently agreed and connected with the Alzheimer’s disease as the literary findings. It is well known that an MRI picture and the pixels are not quantitative by itself. The MRI imaging is primarily for the judgment of anatomy, and mainly the contrast calculation is used for quantitative diagnostic analysis, e.g. mean signal intensity of MRI. Because of the inhomogeneity and other distortion factors, that are presented pending the MRI imaging, I performed experiments in which I defined the small animal MRI equipment repeatability parameter for a defined sequence. My final goal was to prepare a short algorithm which helps to evaluate some statistical probes for each represented animal group.