Multi-component heart reconstruction from volumetric imaging

Computer Tomography (CT) and in particular super fast, 64 and 256 detector CT has rapidly advanced over recent years, such that high resolution cardiac imaging has become a reality. In this paper, we briefly introduce a framework that we have built to construct three dimensional (3D) finite-element and boundary element mesh models of the human heart directly from high resolution CT imaging data. Although, the overall IMAGING-MODELING framework consists of image processing, geometry processing and meshing algorithms, our main focus in this paper will revolve around three key geometry processing steps which are parts of the so-called IMAGING-MODELING framework. These three steps are geometry cleanup or CURATION, anatomy guided annotation or SEGMENTATION and construction of GENERALIZED OFFSET SURFACE. These three algorithms, due to the very nature of the computation involved, can also be thought as parts of a more generalized modeling technique, namely geometric modeling with distance function. As part of the results presented in the paper, we will show that our algorithms are robust enough to effectively deal with the challenges posed by the real-world patient CT data collected from our radiologist collaborators.