Automated Segmentation of the Left Ventricle in Cardiac MRI

By Michael Kaus, Jens von Berg, Wiro J. Niessen, Vladimir Pekar. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2003

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Statistical shape models for 3D medical image segmentation: A review (2009, methodology): “present a more practical solution in (Kaus et al., 2004): After clustering all features into n classes with the k-means algorithm, each landmark is assigned to the cluster containing the largest number of training features from that point.”
A review of segmentation methods in short axis cardiac MR images (2011, background): “LVv - SM Kaus et al. (2004) PCA and energy min.”
Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI (2008, background): “For example (Kaus et al., 2004), demonstrate the usefulness of integrating prior sources of knowledge into a model for robust segmentation.”
Automatic Model-Based Segmentation of the Heart in CT Images (2008, methodology): “[26] applied these deformable models to the segmentation of the LV from MR images using coupling constraints between the endocardial and epicardial surfaces of the model.”