Myocardial segmentation using contour-constrained optical flow tracking

Despite the important role of object tracking using the Optical Flow (OF) in computer graphics applications, it has a limited role in segmenting speckle-free medical images such as magnetic resonance images of the heart. In this work, we propose a novel solution of the OF equation that allows incorporating additional constraints of the shape of the segmented object. We formulate a cost function that include the OF constraint in addition to myocardial contour properties such as smoothness and elasticity. The method is totally different from the common naïve combination of OF estimation within the active contour model framework. The technique is applied to dataset of 20 patients and comparison with manual segmentation shows sensitivity and specificity levels of 93% and 99% respectively is obtained through the challenge validation system. © 2012 Springer-Verlag.