Assessment of separation of functional components with ICA from dynamic cardiac perfusion PET phantom images for volume extraction with deformable surface models

Abstract

We evaluated applicability of ICA (Independent Component Analysis) for the separation of functional components from H215O PET (Positron Emission Tomography) cardiac images. The effects of varying myocardial perfusion to the separation results were investigated using a dynamic 2D numerical phantom. The effects of motion in cardiac region were studied using a dynamic 3D phantom. In this 3D phantom, the anatomy and the motion of the heart were simulated based on the MCAT (Mathematical Cardiac Torso) phantom and the image acquisition process was simulated with the PET SORTEO Monte Carlo simulator. With ICA, it was possible to separate the right and left ventricles in the all tests, even with large motion of the heart. In addition, we extracted the ventricle volumes from the ICA component images using the Deformable Surface Model based on Dual Surface Minimization (DM-DSM). In the future our aim is to use the extracted volumes for movement correction. © Springer-Verlag Berlin Heidelberg 2005.