A sensitive and efficient method for measuring change in cortical thickness using fuzzy correspondence in Alzheimer´s disease

We present a new method for measuring cortical thickness changes on longitudinal magnetic resonance images (MRIs). The method is voxel-based for computational efficiency and sensitivity to subtle changes, but aims for robustness in establishing correspondences by using geometric features that are defined on the cortical skeletons of each scan. In contrast to existing longitudinal methods, our method does not require deformable registration but rather performs cortex-specific, feature-based matching in a confidence-weighted manner, which allows a skeletal point in one scan to be partially matched to multiple points in another scan, thereby enhancing the stability of the matches. Based on comprehensive experiments and statistical analyses on two datasets, our results show that the proposed method demonstrates greater sensitivity to clinically relevant changes than three other state-of-the-art methods and comparable reproducibility.