By Topic

Segmentation of cardiac MR images using - the EM algorithm with a 4D probabilistic atlas and a global connectivity filter

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Lorenzo-Valdes, M. ; Dept. of Comput., Imperial Coll., London, UK ; Rueckert, D. ; Mohiaddin, R. ; Sanchez-Ortiz, G.I.

In this paper an automatic atlas-based segmentation algorithm for 4D cardiac MR images is described. The algorithm is based on the 4D extension of the expectation maximisation (EM) algorithm. The EM algorithm uses a 4D probabilistic cardiac atlas to estimate the initial model parameters and to integrate spatially-varying a-priori information into the classification process. It provides space and time-varying probability maps for the left and right ventricle, the myocardium, and background structures such as the liver, stomach, lungs and skin. The segmentation algorithm also incorporates spatial and temporal contextual information by using 4D Markov Random Fields (MRF). After the classification, the largest connected component of each structure is used as a global connectivity filter that improves the results significantly, especially for the myocardium. Validation against manual segmentations and computation of the correlation between manual and automatic segmentation on 249 3D volumes were calculated. Results show that the procedure can successfully segment the left ventricle (LV) (r=0.96), myocardium (r=0.92) and right ventricle (RV) (r=0.92).

Published in:

Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE  (Volume:1 )

Date of Conference:

17-21 Sept. 2003