Title
Segmentation of cardiac MR volume data using 3D active appearance models
Abstract
Active Appearance Models (AAMs) are useful for the segmentation of cardiac MR images since they exploit prior knowledge about the cardiac shape and image appearance. However, traditional AAMs only process 2D images, not taking into account the 3D data inherent to MR. This paper presents a novel, true 3D Active Appearance Model that models the intrinsic 3D shape and image appearance of the left ventricle in cardiac MR data. In 3D-AAM, shape and appearance of the Left Ventricle (LV) is modeled from a set of expert drawn contours. The contours are then resampled to a manually defined set of landmark points, and subsequently aligned. Appearance variations in both shape and texture are captured using Principal Component Analysis (PCA) on the training set. Segmentation is achieved by minimizing the model appearance-to-target differences by adjusting the model eigen-coefficients using a gradient descent approach. The clinical potential of the 3D-AAM is demonstrated in short-axis cardiac magnetic resonance (MR) images. The method's performance was assessed by comparison with manually-identified independent standards in 56 clinical MR sequences. The method showed good agreement with the independent standards using quantitative indices such as border positioning errors, endo- and epicardial volumes, and left ventricular mass. The 3D AAM method shows high promise for successful segmentation of three-dimensional images in MR.
Year
DOI
Venue
2002
10.1117/12.467185
Proceedings of SPIE
Keywords
Field
DocType
active appearance models,active shape models,point distribution models,principal component analysis
Training set,Computer vision,Gradient descent,Segmentation,Computer science,Active appearance model,Cardiac magnetic resonance,Artificial intelligence,Landmark,Principal component analysis
Conference
Volume
ISSN
Citations 
4684
0277-786X
9
PageRank 
References 
Authors
1.74
0
6
Name
Order
Citations
PageRank
S. C. Mitchell192.08
B.P.F. Lelieveldt21331115.59
Johan G. Bosch365055.66
R. V. Der Geest491.74
J. H. Reiber591.74
Milan Sonka623149.15