3D Ultrasound tracking of the left ventricles using one-step forward prediction and data fusion of collaborative trackers.

Lin Yang(1,2,3), B. Georgescu(3), Yefeng Zheng(3), P. Meer(1), D. Comaniciu(3)

(1)Department of Electrical and Computer Engineering
Rutgers University, Piscataway, NJ 08854, USA

(2)BioImaging Laboratory, Department of Pathology and Laboratory Medicine
UMDNJ-Robert Wood Johnson Medical School
Piscataway, NJ 08855, USA

(3)Integrated Data Systems, Siemens Corporate Research
755 College Road East, Princeton, NJ 08540

Tracking the left ventricle (LV) in 3D ultrasound data is a challenging task because of the poor image quality and speed requirements. Many previous algorithms applied standard 2D tracking methods to tackle the 3D problem. However, the performance is limited due to increased data size, landmarks ambiguity, signal drop-out or non-rigid deformation. In this paper we present a robust, fast and accurate 3D LV tracking algorithm. We propose a novel one-step forward prediction to generate the motion prior using motion manifold learning, and introduce two collaborative trackers to achieve both temporal consistency and failure recovery. Compared with tracking by detection and 3D optical flow, our algorithm provides the best results and subvoxel accuracy. The new tracking algorithm is completely automatic and computationally efficient. It requires less than 1.5 seconds to process a 3D volume which contains 4,925,440 voxels.

2008 Computer Vision and Pattern Recognition Conference , Anchorage, Alaska, June 2008.

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