This work provides methods to measure and analyze features of atrial electrograms - especially
complex fractionated atrial electrograms (CFAEs) - mathematically. Automated classification of
CFAEs into clinical meaningful classes is applied and the newly gained electrogram information
is visualized on patient specific 3D models of the atria. Clinical applications of the
presented methods showed that quantitative measures of CFAEs reveal beneficial information
about the underlying arrhythmia.
