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This paper presents an automatic method to find and segment the boarders of the left and right ventricles (LV and RV) from the middle short axis (SA) slice of a functional cardiac MRI study. The segmentation is implemented using a new atlas-based registration framework which is able to integrate boundary, intensity and anatomical information. The method is shown to be accurate, robust and reliable...
Model-based medical image analysis allows high level information to guide image segmentation. However, most model-based methods rely on evolution methods which may become trapped in local minima. Graph cuts have been proposed for image segmentation problems where the cost of the cut corresponds to an energy function which is then globally minimized. However, it has been difficult to include high level...
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