Three-Dimensional Model-Based Segmentation in Echocardiography Using High Temporal Tissue and Blood Flow Information.

Accurate 3-D surface segmentation is a challenging task in echocardiography because of the relatively low image quality. We introduce a new method for 3-D segmentation of the endocardium involving temporal decorrelation of echo signals originating from tissue and blood using radiofrequency (RF) signals acquired in 3-D Doppler mode. Temporal features were extracted in 3-D Doppler mode, where a sequence of RF lines is recorded for each image line. Each set of RF lines is highly correlated because of the high pulse repetition frequency. However, for high blood flow, the RF signals will decorrelate over time in contrast to the endocardium, which will remain relatively highly correlated over time. These decorrelation features permit differentiation between myocardial tissue and blood flow. We describe an implementation of a 3-D segmentation model in which temporal information is used as external constraint. The model was validated in a phantom and in vivo in healthy volunteers (n = 5). The phantom study revealed that the model successfully segmented the artificial blood lumen even for low flow velocity and illustrated the sensitivity of the segmentations to flow rate. In healthy volunteers, high Dice similarity indices indicate that 3-D segmentation of the endocardial border in vivo is feasible.