Speckle filtering of ultrasound images using a modified non‐linear diffusion model in non‐subsampled shearlet domain

Abstract

Speckle filtering is of great interest for the ultrasound medical images in which various noises and artefacts are introduced because of various limitations of the acquisition systems and techniques. Speckle is a prime factor to degrade the quality and most importantly, texture information present in the ultrasound images. This study presents a despeckling method based on a modified non-linear diffusion model and non-subsampled shearlet transform (NSST). As a new image representation method with the different features of localisation, directionality and multiscale, the NSST is utilised to provide the effective representation of the image coefficients. The modified anisotropic diffusion is applied to the noisy coarser NSST coefficients to improve the denoising efficiency and preserve the edge features effectively. In the diffusion process, the nonlocal pixel information is incorporated to evaluate the gradient of eight connected neighbouring pixels with an adaptive grey variance. The performance of the proposed method is evaluated for both the standard test and real ultrasound images. Experimental results show that the proposed method produces better results of noise suppression with the preservation of more edges compared with several existing methods.

Carotid artery ultrasound image analysis: A review of the literature

“…In the multi-scale sub-bands, the quantum-inspired noise values are considered to be present. 64,65 The process to be followed are log transform, decomposition by DTCWT, estimation of noise variance, σ, k , shrinking of the coefficients depending on quantum-inspired adaptive threshold function, updating the coefficients, inverse DTCWT and exponential to remove the log. Another method which uses wavelet-based Bayesian processor states that the ultrasound image has the property of heteroscedasticity and non-Gaussian statistics in it.…”

“…The author’s method completely user-independent layer extraction based on signal analysis (CULEXsa) 65 had artifact issues. The approach in that was to automatically extract the boundary of near and far adventitia walls followed by gradient-based segmentation and snake contouring.…”

A Median Filter With Evaluating of Temporal Ultrasound Image for Impulse Noise Removal for Kidney Diagnosis

“…Li & Liu in their research used dynamic filtering techniques particularly for image enhancement [9]. Gajanand Gupta compared the improved technique of median filter to median and mean filter techniques [5]. The median filter is among the most widely used nonlinear spatial domain filters.…”

“…The presence of these kinds of noises prevents the precision of the clinical diagnosis by reducing the quality of vision. In addition, diagnosis that consumes more time and post-processing, such as segmentation and extraction of data, is becoming very difficult [5]. Noise reduction or denouncement of US images therefore becomes a necessary necessity without the impact of edges and textures in the images.…”

Sparse PDE for SAR image speckle suppression

“…Although optical images and SAR images have different scattering characters, many denoising methods for optical images have been extended to speckle suppression. These methods include wavelet method [5, 6], variational method [7–10], partial differential equation (PDE) method [11–15], statistical method [16–19]. Different approaches have different starting points.…”