The use of numerical methods in clinical medicine has grown exponentially over the past decade. This is particularly true in clinical cardiac electrophysiology (EP), which is focused on the diagnosis, prevention and treatment of heart rhythm abnormalities. Part of the reason for this is the suitability of cardiac rhythm pathology to numerical modeling. At the tissue level, the mechanisms of electrical propagation within the heart are relatively deterministic both in health and during arrhythmias [31]. As a result, for many applications, there is remarkable correlation between prediction and measurement [30]. Another reason is the availability of detailed anatomical and physiologic imaging data in cardiology, including: echocardiography (transthoracic, transesophageal, and intracardiac), computed tomography (CT), magnetic resonance imaging (MRI), nuclear medicine, and positron emission tomography.