  We propose an ultrasound speckle filtering method for not only preserving
various edge features but also filtering tissue-dependent complex speckle
noises in ultrasound images. The key idea is to detect these various edges
using a phase congruence-based edge significance measure called phase asymmetry
(PAS), which is invariant to the intensity amplitude of edges and takes 0 in
non-edge smooth regions and 1 at the idea step edge, while also taking
intermediate values at slowly varying ramp edges. By leveraging the PAS metric
in designing weighting coefficients to maintain a balance between
fractional-order anisotropic diffusion and total variation (TV) filters in TV
cost function, we propose a new fractional TV framework to not only achieve the
best despeckling performance with ramp edge preservation but also reduce the
staircase effect produced by integral-order filters. Then, we exploit the PAS
metric in designing a new fractional-order diffusion coefficient to properly
preserve low-contrast edges in diffusion filtering. Finally, different from
fixed fractional-order diffusion filters, an adaptive fractional order is
introduced based on the PAS metric to enhance various weak edges in the
spatially transitional areas between objects. The proposed fractional TV model
is minimized using the gradient descent method to obtain the final denoised
image. The experimental results and real application of ultrasound breast image
segmentation show that the proposed method outperforms other state-of-the-art
ultrasound despeckling filters for both speckle reduction and feature
preservation in terms of visual evaluation and quantitative indices.
