Region-based endocardium tracking on real-time three-dimensional ultrasound.
Matrix-phased array transducers for real-time 3-D ultrasound enable fast, noninvasive visualization of cardiac ventricles. Typically, 3-D ultrasound images are semiautomatically segmented to extract the left ventricular endocardial surface at end-diastole and end-systole. Automatic segmentation and propagation of this surface throughout the entire cardiac cycle is a challenging and cumbersome task. If the position of the endocardial surface is provided at one or two time frames during the cardiac cycle, automated tracking of the surface over the remaining time frames could reduce the workload of cardiologists and optimize analysis of 3-D ultrasound data. In this paper, we applied a region-based tracking algorithm to track the endocardial surface between two reference frames that were manually segmented. To evaluate the tracking of the endocardium, the method was applied to 40 open-chest dog datasets with 484 frames in total. Ventricular geometry and volumes derived from region-based endocardial surfaces and manual tracing were quantitatively compared, showing strong correlation between the two approaches. Statistical analysis showed that the errors from tracking were within the range of interobserver variability of manual tracing. Moreover, our algorithm performed well on ischemia datasets, suggesting that the method is robust-to-abnormal wall motion. In conclusion, the proposed optical flow-based surface tracking method is very efficient and accurate, providing dynamic "interpolation" of segmented endocardial surfaces.
Duan
Qi
Q
Department of Biomedical Engineering, Columbia University, New York, NY, USA. qd2002@columbia.edu
Angelini
Elsa D
ED
Herz
Susan L
SL
Ingrassia
Christopher M
CM
Costa
Kevin D
KD
Holmes
Jeffrey W
JW
Homma
Shunichi
S
Laine
Andrew F
AF
D000465:Algorithms; D003971:Diastole; D019561:Echocardiography, Four-Dimensional / Q000379:methods*; D004699:Endocardium / Q000000981:diagnostic imaging* / Q000502:physiology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D017202:Myocardial Ischemia / Q000000981:diagnostic imaging; D012680:Sensitivity and Specificity; D013599:Systole