DESPECKLEING PROSTATE ULTRASONOGRAMS USING PDE WITH WAVELET

J. Ramesh, R. Manavalan
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引用次数: 2

Abstract

: Prostate cancer is the leading cause of death for men, since the cause of the disease is mysterious and its early detection is also monotonous. Ultrasound (US) is the most popular tool to detect the human organ glands and also used to diagnose the prostate cancer. Speckle noise is an inherent nature of ultrasound images, which degrades the image quality. So far, No specific filter is available to suppress the speckle noise in prostate image. In this paper, a novel despeckling method PDE with Wavelet is presented for prostate US images. The enhancement method is evaluated by using standard measures like Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR) and Edge Preservation Index (EPI). Further, the despeckling approaches' is also evaluated time and space complexity. From the results, it is observed that the filtering method PDE with Wavelet is superior to PDE in terms of denoising and also preserving the information content.
用小波变换PDE解标前列腺超声
:前列腺癌症是男性死亡的主要原因,因为这种疾病的病因很神秘,早期检测也很单调。超声(US)是最流行的检测人体器官腺体的工具,也用于诊断前列腺癌症。散斑噪声是超声图像的固有特性,它会降低图像质量。到目前为止,还没有专门的滤波器来抑制前列腺图像中的斑点噪声。本文提出了一种新的基于小波的前列腺超声图像去斑点方法PDE。通过使用均方误差(MSE)、峰值信噪比(PSNR)和边缘保持指数(EPI)等标准度量来评估增强方法。此外,还评估了去斑点方法的时间和空间复杂性。从结果中可以看出,小波滤波方法PDE在去噪和保留信息内容方面优于PDE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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