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(b) Gradient Vector Flow of U-Image.

For example, generalized gradient vector flow [11], harmonic gradient vector flow [12], motion gradient vector flow [13] and generalized dynamic directional gradient vector flow [14], but none of these are able to resolve all of the problems mentioned above.

Tissue components are segmented automatically using generalized gradient vector flow active contours.

These models rely on accurate time resolved measurements of scalar and vector flow variables.

The second term, the image energy term, is calculated using gradient vector flow (GVF) [12].

Unlike traditional gradient vector flow snake, the improved gradient vector flow snake adopts anisotropic diffusion and a four directions edge operator to solve the blurry boundary and edge shifting problem.

To set the initial contour of the gradient vector flow snake automatically, we design an intra-frame centroids tracking algorithm.

Olivieri et al. [12] proposed a spatiotemporal motion feature to represent activities termed motion vector flow instance (MVFI) templates.

Eventually, this function can be regarded as a 2D vector flow describing the offset of the images.

The external force is computed as gradient vector flow (GVF), i.e. the diffusion of the gradient vectors.

The interleaved transmissions ensure both a highly sensitive vector flow image and a high-resolution B-mode images.