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Reduction of speckle noise from medical images using principal component analysis image fusion

机译:使用主成分分析图像融合减少医学图像中的斑点噪声

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Images captured by different medical devices contain intrinsic artefacts, like ultrasound, CT, MRI images often contain speckle noise, which is the result of the destructive and constructive coherent summation of echoes. In these images, the speckle noise must be reduced cautiously as it also contains diagnostic information. Thus the despeckling algorithms should reduce speckle in homogeneous areas of the image and edges in the image should be preserved. In this paper a method to reduce the speckle noise is proposed which uses the concept of fusion. The performance of the proposed algorithm is quantified by calculating measures like MSE, SNR, PSNR and MSSI, which gives information about the extent of feature preservation and denoising.
机译:由不同医疗设备捕获的图像包含固有伪像,例如超声,CT,MRI图像通常包含斑点噪声,这是回声的破坏性和建设性相干求和的结果。在这些图像中,斑点噪声必须谨慎降低,因为它还包含诊断信息。因此,去斑点算法应当减少图像的均匀区域中的斑点,并且应当保留图像中的边缘。本文提出了一种利用融合的概念来减少斑点噪声的方法。通过计算MSE,SNR,PSNR和MSSI等度量来量化所提出算法的性能,该度量可提供有关特征保留和去噪程度的信息。

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