Knowledge Based Imaging is suggested as a method to distinguish blood from tissue signal in transthoracial echocardiography. Parametric model for the autocorrelation functions for turbulent blood flow and slowly moving tissue are augmented for in this paper. The model also includes the presence of stationary clutter noise and system white noise. Knowledge Based Imaging utilizes the maximum likelihood function to classify blood and tissue signal. In amplitude imaging blood and tissue are separated by their difference in signal powers. This effect is also present in Knowledge Based Imaging. In addition, this method utilizes the fact that blood flow is turbulent and moves faster than tissue. Some images of Knowledge Based Imaging with different parameter settings are visually compared with Second-Harmonic Imaging, Fundamental Imaging and Bandwidth Imaging [1].
展开▼
