Automatic 4D endocardium segmentation using hierarchical registration and model guided level set segmentation

For the analysis of shape variations of the heart and the cardiac motion in a clinical environment it is necessary to segment a large amount of data in order to be able to build statistically significant models. Hence it has been the objective of this project to find and develop methods that allow the creation of a fully automatic segmentation pipeline for the 4D segmentation of the endocardium in ECG-triggered MRI images. For this purpose a combination of various image processing techniques from the fields of segmentation, modeling and image registration have been used and extended to create a segmentation pipeline that reduces the need for supplementary manual correction of the segmented labels to a minimum.