A method for detecting interstructural atrophy correlation in MRI brain images

Distinguishing neurodegenerative diseased patients (e.g., suffering from Alzheimer¿s Disease (AD)) from healthy individuals with the aid of MRI images is one of the challenges that need to be addressed in the field of Computational Anatomy (CA). A crucial feature in the analysis is the rate of atrophy of brain structures like the hippocampus or the ventricles. Until recently, analysis of atrophy rate has been restricted mainly to „localized atrophy¿, i.e. atrophy within one brain structure. Distinguishing correlations of atrophy rates between different brain structures could possibly provide additional information about the disease process. Therefore, in this paper, we propose a method to measure and analyze correlations of atrophy rate between hippocampus and ventricles with the aid of some correlation parameters. We combine the parameters that we thus obtain with some local atrophy rate parameters into a multidimensional vector, and use various vector classification methods to analyze the atrophy process with the aid of MRI brain volumes from the ADNI database. We obtain a good agreement between our classification results and the ground truth data. The analysis is facilitated with the aid of a specially designed graphical user interface