Novel image enhancement approaches for despeckling in ultrasound images for fibroid detection in human uterus

IF 1.1 Q3 COMPUTER SCIENCE, THEORY & METHODS Open Computer Science Pub Date : 2021-01-01 DOI:10.1515/comp-2020-0140
K. T. Dilna, Jude Hemanth Duraisamy
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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.
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用于子宫肌瘤检测的超声图像斑点增强新方法
超声是一种被广泛应用的医学成像技术。它的工作原理是考虑组织的回声的基本理论。然而,信号相关噪声如斑点的出现破坏了超声图像的实用性。散斑噪声受图像组织组成和图像参数的影响。它降低了许多图像处理步骤的有效性,降低了人类对超声图像细节的感知。在许多医学图像处理方法中,去斑点是分割和特征提取前的预处理步骤。虽然提出了许多散斑抑制滤波器,但在结合多种技术的同时,需要保留一些散斑诊断信息。在超声图像恢复中,通过保留边缘和附加特征来去除斑点噪声是一项极具挑战性的任务。本文对超声肌瘤图像的斑点噪声降噪进行了全面的描述和比较。在超声扫描图像上应用了许多滤波器,并用一些统计度量来标记其性能。尽管有几种去斑滤波器可以减少斑点,但它们都不能很好地用于超声扫描图像。比较了超声图像去斑的质量指标,如均方误差、峰值信噪比和信噪比。
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来源期刊
Open Computer Science
Open Computer Science COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
4.00
自引率
0.00%
发文量
24
审稿时长
25 weeks
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