This paper explores the viability of applying 3D optical flow techniques on 3D heart sequences to diagnose cardiac abnormalities and disease. Tagged magnetic resonance imaging (TMRI) is a non-invasive method to visualize in vivo myocardium motion during a cardiac cycle. By tracking the 3D trajectories of tagged material points it is possible to construct a volumetric model of the heart. Specifically, we use generated meshless deformable models (MDM) which describe an object as a point cloud inside the object boundary. We extend the 2D least squares and regularization approaches of Lucas and Kanade to 3D in order capture the flow, specifically the contraction and expansion of various parts of the heart motion. Features are extracted from this flow and a rudimentary SVM is used to classify unhealthy hearts.
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