Hybrid optical flow and segmentation technique for LV motion detection

In this paper we propose a hybrid technique for detection of left ventricle motion and its segmentation from image sequence of a beating human heart. Each point on the surface of the cardiac wall moves at specific trajectory within 3D space over time. Accurate estimation of the cardiac wall motion has been shown to be very important in studying coronary diseases, such as ischemia. The proposed technique has three steps. Optical flow is computed from the sequence of images using gradient based method, then information on movement is introduced to the segmentation algorithm, and finally characteristic points along segmented boundary are detected by matching shape properties in two consecutive time frames. The estimates of optical flow for those points are used as additional constraints in the second run of the optical flow algorithm. We present experimental results obtained by the proposed algorithm and compare the optical flow fields after both runs. The image sequence of segmented LV is presented with estimates of motion at the boundaries. Experiments have shown encouraging results.