Abstract

Abstract Ultrasonography is an extensively used medical imaging technique for multiple reasons. It works on the basic theory of echoes from the tissues under consideration. However, the occurrence of signal dependent noise such as speckle destroys utility of ultrasound images. Speckle noise is subject to the composition of image tissue and parameters of image. It reduces the effectiveness of many image processing steps and decreases human perception of fine details form ultrasound images. In many medical image processing methods, despeckling is used as the preprocessing step before segmentation and feature extraction. Many speckle reduction filters are proposed but while combining many techniques some speckle diagnostic information should be preserved. Removal of speckle noise from ultrasound image by preserving edges and added features is a great challenging task in ultrasound image restoration. This paper aims at a comprehensive description and comparison of reduction of speckle noise of ultrasound fibroid image. Many filters are applied on ultrasound scanned images and the performance is marked in terms of some statistical measures. Even though several despeckling filters are there for speckle reduction, all are not good for ultrasound scanned images. A comparison of quality measures such as mean square error, peak signal-to-noise ratio, and signal-to-noise ratio is done in ultrasound images in despeckling.

Highlights

  • Ultrasonography is an extensively used medical imaging technique for multiple reasons

  • Ultrasound scanned uterus fibroid image is used as input image and it is transformed into gray scale

  • Two different scalar filters, four adaptive filter methods (Weiner filter, speckle reducing anisotropic diffusion (SRAD), and Lee and Kaun filter), wavelet transformation filter, and homomorphic filter are applied on transformed fibroid image

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Summary

Introduction

Abstract: Ultrasonography is an extensively used medical imaging technique for multiple reasons. It works on the basic theory of echoes from the tissues under consideration. Speckle noise is subject to the composition of image tissue and parameters of image. It reduces the effectiveness of many image processing steps and decreases human perception of fine details form ultrasound images. In many medical image processing methods, despeckling is used as the preprocessing step before segmentation and feature extraction. Even though several despeckling filters are there for speckle reduction, all are not good for ultrasound scanned images. A comparison of quality measures such as mean square error, peak signal-tonoise ratio, and signal-to-noise ratio is done in ultrasound images in despeckling

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