Development of a Heart Motion Tracking System using Non-invasive Imaging Data

Cardiac motion can be monitored non-invasively for the assessment of cardiovascular function by using medical imaging systems and motion tracking algorithms. Existing tracking approaches require a priori understanding of the non-rigid motion of the target system , which could change over multiple cardiac cycles and lead to tracking failures. The purpose of this research is to develop the algorithm and software , with computer vision techniques , to continuously track the motion of a user-defined region of the heart images. The proposed algorithm improves upon existing techniques because it does not require an underlying motion model , it quantifies the quality of tracking , and it can recover from a failed tracking estimate. The motion estimation of a non-rigid system will be done by a piecewise tracking approach that breaks up the region of interest into several small segments (patches) , which can be approximated with interconnected pseudo-rigid segments. These segments will be initialized based on two criteria: 1) motion within a segment must follow the pseudo-rigid body model; and 2) motion in neighboring segments must be similar to each other. Segments are subsequently tracked as pseudo-rigid bodies , and the criteria described above are also used to detect failures in tracking. If a failure were to occur , the tracking algorithm will be reinitialized automatically. This algorithm was shown to be accurate and efficient , and has been tested on several heart motion data sets