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Region Descriptors to Extricate Renal Calculi by Discerning Artifacts from Ultra

机译:通过识别超人为假象而消除肾脏结石的区域描述符

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The study presents a new technique to identify kidney stones and differentiate it from artifacts from an ultra sound scanned image. Image analysis plays vital role in medical diagnosis. Analysing texture is a major source of discrimination in image analysis. There are situations when artifacts are mistaken for kidney stones in Medical scan using Ultra sound technique. We are proposing a new approach wherein the kidney stones are differentiated from artifacts using various shape descriptive parameters. Various descriptors like Compactness, Dispersion, Smoothness and third moment are used in our method to differentiate artifacts and stones from ultrasound images. Basic regional descriptor characterizes the geometric properties of ROI (Region of Interest) whereas Invariant moment concentrates on the density of ROI. Initially the US image is polished using a Combinational approach of noise removal and this image is taken as input for our further analysis. Pre-processing is done to minimize the occurrence of artifacts. The potential calculi are extracted and the validity is tested using the above specified parameters. Test results show convincing difference in values between Calculi and Artifact. The suggested method efficiently helped in identifying Renal Calculi from Ultra sound Images.
机译:这项研究提出了一种新技术,可以识别肾结石并将其与超声扫描图像中的伪影区分开。图像分析在医学诊断中起着至关重要的作用。分析纹理是图像分析中歧视的主要来源。在某些情况下,使用超声波技术在医学扫描中将伪影误认为肾结石。我们正在提出一种新方法,其中使用各种形状描述参数将肾结石与伪影区分开。在我们的方法中,使用了诸如紧实度,色散,平滑度和三次矩之类的各种描述符来区分伪影和结石与超声图像。基本的区域描述符描述了ROI(感兴趣区域)的几何特性,而不变矩则集中在ROI的密度上。最初,使用Combinational噪声消除方法对美国图像进行了抛光,然后将该图像用作我们进一步分析的输入。进行预处理以最大程度地减少伪影的发生。使用上述指定参数提取潜在的结石并测试有效性。测试结果表明,计算值与伪像之间的值存在令人信服的差异。所建议的方法有效地帮助从超声图像中识别肾结石。

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