Tracking of left ventricles in 3D echocardiography is a challenging topic because of the poor quality of ultrasound images and the speed consideration. In this paper, a fast and accurate learning based 3D tracking algorithm is presented. A novel one-step forward prediction is proposed to generate the motion prior using motion manifold learning. Collaborative trackers are introduced to achieve both temporal consistence anproc biomedical optical ima image segmentation cellular biophys fluores biology comd tracking robustness. The algorithm is completely automatic and computationally efficient. The mean point-to-mesh error of our algorithm is 1.28 mm. It requires less than 1.5 seconds to process a 3D volume (160 x 148 x 208 voxels).
['Lin Yang', 'B. Georgescifi', 'Yefeng Zheng', 'David J. Foran', 'Dorin Comaniciu']
A fast and accurate tracking algorithm of left ventricles in 3D echocardiography