A real-time cardiac surface tracking system using Subspace Clustering
Catheter based radio frequency ablation of atrial fibrillation requires real-time 3D tracking of cardiac surfaces with sub-millimeter accuracy. To best of our knowledge, there are no commercial or non-commercial systems capable to do so. In this paper, a system for high-accuracy 3D tracking of cardiac surfaces in real-time is proposed and results applied to a real patient dataset are presented. Proposed system uses Subspace Clustering algorithm to identify the potential deformation subspaces for cardiac surfaces during the training phase from pre-operative MRI scan based training set. In Tracking phase, using low-density outer cardiac surface samples, active deformation subspace is identified and complete inner & outer cardiac surfaces are reconstructed in real-time under a least squares formulation.