Figure 1:

An illustration of the different steps of the noise-bias suppression algorithm. (a, b) display the acquired Doppler ensemble, and the corresponding clutter-filtered Doppler ensemble (CFDE), respectively. The corresponding LSTC image (d) is computed from the CFDE (c) by estimating spatiotemporal correlation in local 3D kernels (red) as defined in Eqn. 3. (e,g) displays the binary mask computed by greyscale thresholding of the LSTC image, which is inherently normalized between 0-1. The black and white regions corresponds to the location of the flow and noise pixels, respectively. The synthetic noise image (h) is generated from a single clutter filtered image, by replacing its vessel pixels by randomly selected noise from its local 3D neighborhood in the corresponding CFDE (f). (i) displays the low-rank approximation of the synthetic noise image (h), which is subsequently smoothened using a 2D least-square based plane-fit algorithm to generate the final noise field (j). The final PD image (l) is obtained by suppressing the estimated noise field (j) in the original PD image (k).