Analysis of four-dimensional cardiac data sets using skeleton-based segmentation

Abstract

Computer-aided analysis of four-dimensional tomography data has become an important tool in modern cardiology. In order to examine the capability and health of a patient’s cardiac system, scans are taken at a number of time points evenly distributed over one cardiac cycle. A key task for understanding the dynamics involved within a recorded cardiac cycle is to segment the acquired data to identify objects of interest in each volume of the sequence. This paper presents an algorithm to segment the heart muscle and the left ventricle from a sequence of cardiac CT images using only a minimum of user interaction. Furthermore, the paper introduces methods to process the segmentation result for extraction of important properties of the cardiac cycle, which are helpful for diagnosis.