Predicting and increasing the expected battery lifetime is one of the major objectives in state-of-the-art battery research. Until now, the highly complex mechanisms taking place during cyclic aging are only understood to a certain extent. In the present paper, pristine and cyclically aged battery electrodes are considered and the relationship between their microstructure and functionality is investigated. For this purpose, three-dimensional image data obtained by synchrotron tomography is preprocessed by a novel data-driven trinarization approach based on k-means clustering. This allows us to explicitly distinguish between active material, pore space and the phase consisting of binder and conductive additives. This three-phase reconstruction is completed by a segmentation of active material particles, which enables a comprehensive statistical analysis of the electrode morphology. In addition, the investigation of numerous image characteristics together with electrochemical measurements contributes to a deeper understanding of the underlying aging mechanisms.