In this paper we present a novel approach to the problem of fitting a 4D statistical shape model of the myocardium to
cardiac MR and CT image sequences. The 4D statistical model has been constructed from 25 cardiac MR image sequences
from normal volunteers. The model is controlled by two sets of shape parameters. The first set of shape parameters
describes shape changes due to inter-subject variability while the second set of shape parameters describes shape changes
due to intra-subject variability, i.e. the cardiac contraction and relaxation. A novel fitting approach is used to estimate the
optimal parameters of the cardiac shape model. The fitting of the model is performed simultaneously for the entire image
sequences. The method has been tested on 5 cardiac MR image sequences. Furthermore, we have also tested the method
using a cardiac CT image sequence. The result demonstrate that the method is not only able to fit the 4D model to cardiac
MR image sequences, but also to cardiac image sequences from a different modality (CT).
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.