Enhancement of images corrupted with signal dependent noise: Application to ultrasonic imaging

An adaptive filter for smoothing images corrupted by signal dependent noise is presented. The filter is mainly developed for speckle suppression in medical B-scan ultrasonic imaging. The filter is based on mean filtering of the image using appropriately shaped and sized local kernels. Each filtering kernel, fitting to the local homogeneous region, is obtained through local statistics based region growing. Performance of the proposed scheme have been tested on a B-scan image of a standard tissue-mimicking ultrasound resolution phantom. The results indicate that the filter effectively reduces the speckle while preserving the resolvable details. The performance figures obtained through computer simulations on the phantom image are presented in a comparative way with some existing speckle iippression schemes

An adaptive speckle suppression filter for medical ultrasound imaging

Cataloged from PDF version of article.An adaptive smoothing technique for speckle suppression in medical B-scan ultrasonic imaging is presented. The technique is based on filtering with appropriately shaped and sized local kernels. For each image pixel, a filtering kernel, which fits to the local homogeneous region containing the processed pixel, is obtained through a local statistics based region growing technique. Performance of the proposed filter has been tested on the phantom and tissue images. The results show that the filter effectively reduces the speckle while preserving the resolvable details. The simulation results are presented in a comparative way with two existing speckle suppression methods. © 1995 IEE

FPGA based implementation of low complex adaptive speckle suppression filter for B-mode medical ultrasound images

Speckles are considered as noise, which masks the fine information present in B-mode ultrasound images. Speckles appears as small snakes and dense granular like structures which has serious impact on visual perception of an image. Adaptive filter based on local statistics of an image is used to enhance the image by suppressing the noise. Adaptive speckle suppression filter enhance the image by reducing the variance between intrapixel intensities in homogeneous regions and preserving variance across interpixel intensities across the nonhomogeneous regions. In this paper, we implemented low complex adaptive speckle suppression filter on FPGA based kintex7 board. The performance of the filter is evaluated by plotting the pixel variations of original image with filtered image of an ultrasound phantom. The results show that proposed algorithm can be implemented on mobile ultrasound platforms due to 50% less computations needed per pixel compared to traditional adaptive speckle suppression algorithms, which aids better diagnosis for healthcare

Speckle Suppression in Ultrasonic Images Based on Undecimated Wavelets

An original method to denoise ultrasonic images affected by speckle is presented. Speckle is modeled as a signal-dependent noise corrupting the image. Noise reduction is approached as a Wiener-like filtering performed in a shift-invariant wavelet domain by means of an adaptive rescaling of the coefficients of an undecimated octave decomposition. The scaling factor of each coefficient is calculated from local statistics of the degraded image, the parameters of the noise model, and the wavelet filters. Experimental results demonstrate that excellent background smoothing as well as preservation of edge sharpness and fine details can be obtained

A robust detail preserving anisotropic diffusion for speckle reduction in ultrasound images

<p>Abstract</p> <p>Background</p> <p>Speckles in ultrasound imaging affect image quality and can make the post-processing difficult. Speckle reduction technologies have been employed for removing speckles for some time. One of the effective speckle reduction technologies is anisotropic diffusion. Anisotropic diffusion technology can remove the speckles effectively while preserving the edges of the image and thus has drawn great attention from image processing scientists. However, the proposed methods in the past have different disadvantages, such as being sensitive to the number of iterations or low capability of preserving the details of the ultrasound images. Thus a detail preserved anisotropic diffusion speckle reduction with less sensitive to the number of iterations is needed. This paper aims to develop this kind of technologies.</p> <p>Results</p> <p>In this paper, we propose a robust detail preserving anisotropic diffusion filter (RDPAD) for speckle reduction. In order to get robust diffusion, the proposed method integrates Tukey error norm function into the detail preserving anisotropic diffusion filter (DPAD) developed recently. The proposed method could prohibit over-diffusion and thus is less sensitive to the number of iterations</p> <p>Conclusions</p> <p>The proposed anisotropic diffusion can preserve the important structure information of the original image while reducing speckles. It is also less sensitive to the number of iterations. Experimental results on real ultrasound images show the effectiveness of the proposed anisotropic diffusion filter.</p