Personalized computational cardiac models are emerging as an important tool for studying
cardiac arrhythmia mechanisms, and have the potential to become powerful instruments for
guiding clinical anti-arrhythmia therapy. In this article, we present the methodology for
constructing a patient-specific model of atrial fibrosis as a substrate for atrial fibrillation. The
model is constructed from high-resolution late gadolinium-enhanced magnetic resonance
imaging (LGE-MRI) images acquired in vivo from a patient suffering from persistent atrial …