Heart disease is the leading cause of death in the modern world. Cardiac imaging is
routinely applied for assessment and diagnosis of cardiac diseases. Computerized image …

In the present paper we describe the automatic construction of a statistical shape model of
the whole heart built from a training set of 100 Multi-Slice Computed Tomography (MSCT) …

In this paper, the current status of cardiac image registration methods is reviewed. The
combination of information from multiple cardiac image modalities, such as magnetic …

Domain knowledge about the geometrical properties of cardiac structures is an important
ingredient for the segmentation of these structures in medical images or for the simulation of …

In this paper, we present a novel registration algorithm for locally affine registrations. This
method preserves the anatomical and intensity class relationships between the local …

Purpose Statistical shape models have shown improved reliability and consistency in
cardiac image segmentation. They incorporate a sufficient amount of a priori knowledge …

Statistical shape models (SSMs) have been widely employed in cardiac image
segmentation. However, in conditions that induce severe shape abnormality and …

Automatic image processing methods are a pre-requisite to efficiently analyze the large
amount of image data produced by computed tomography (CT) scanners during cardiac …

We describe a new 3-D statistical shape model of the heart consisting of atria, ventricles and
epicardium. The model was constructed by combining information on standard short-and …

This paper proposes a system to automatically segment the left ventricle in cardiac MR cine
images. Individual frames are segmented using a shortest path algorithm and temporal …