脑NCCT图像不同去噪技术的比较研究

Simarjeet Kaur, Jimmy Singla, Nikita Nikita
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引用次数: 2

摘要

医学图像在采集技术或患者运动过程中经常受到噪声和伪影的影响。有时放射科医生无法从有噪声的图像中做出有用和准确的结论。本研究的主要目的是对高斯滤波、中值滤波、双边滤波、非局部均值滤波(NLM)、全变差(TV)各向异性扩散(AD)、BM3D方法等各种去噪技术对脑NCCT(非对比计算机断层扫描)图像进行比较。本研究的主要重点是对这些技术进行比较分析,不仅可以去除而且可以保留大脑NCCT图像的边缘。实验结果表明,BM3D在PSNR值方面表现最好,其次是全变分法和各向异性扩散法。然而,边缘的损失和其他精细的细节是存在的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative study of different denoising techniques on Brain NCCT images
Medical images often get affected by noise and artifacts while acquisition techniques or patient’s movement. Some time radiologists unable to make useful and accurate conclusion from noisy images. The main aim of this study is to conduct a comparative measure of various denoising techniques such as Gaussian filter, Median filter, Bilateral filter, Non-Local Mean filter(NLM), Total Variation (TV) Anisotropic Diffusion (AD), BM3D method, on brain NCCT(Non-Contrast computed tomography) images. The prime focus of this research is to make comparative analysis of these techniques not merely to remove but also to preserve edges of brain NCCT images. The experimental results present that BM3D shows the best performance in terms of PSNR value, followed by total variation method and anisotropic diffusion method in terms of removal of noise. However marginal loss of edges and other fine details are there.
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