Automated Tag Tracking Using Gabor Filter Bank, Robust Point Matching, and Deformable Models

• Published in: Functional Imaging and Modeling of the Heart pp. 22 - 31
• Main Authors: Chen, Ting, Chung, Sohae, Axel, Leon
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Deformable Model; Gabor Filter; Motion Tracking; Robust Point Matching; Tagged MRI
• ISBN: 9783540729068; 3540729062
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-72907-5_3

Tagged Magnetic Resonance Imaging (tagged MRI or tMRI) provides a means of directly and noninvasively displaying the motion of the myocardium. Reconstruction of the motion field is needed for quantitative analysis of important clinical information, e.g., the myocardial strain. In this paper, we present a two-step method for this task. First, we use a Gabor filter bank to generate a corresponding phase map of tMRI images. Second, deformable models are initialized at the discontinuities in the wrapped phase map, and are deformed under the influence of the image gradient to track the motion of tags. Unlike previous approaches, a Robust Point Matching (RPM) module has been integrated into the model evolution to avoid false tracking results caused by 1) through-plane motion, and 2) small tag spacing. The method has been tested on a numeric phantom, as well as in vivo heart data. The experimental results show that the new method has a good performance on both synthetic and real data, and has the potential to be used in clinical applications.