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Figure 1 An assisted border detection algorithm was employed to segment the myocardium from the rest of the ultrasound image. An exponential curve-fitting function of the form—I(t) = A(1 – exp–ßt)—was fit to the intensity vector from each pixel position in the segmented cine loop, where I(t) represents the intensity of a pixel as a function of time; A represents the intensity of full myocardial replenishment; and ß represents the rate constant of intensity change. The parameters of A and ß were automatically tabulated according to the pixel position and scaled, and a color map was applied to generate parametric images (four panels on the right) of blood volume (A image), blood velocity (ß image), and myocardial blood flow (A x ß image) of each pixel in the myocardium. A goodness-of-fit map for the data was also generated by the algorithm.
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