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Speckle noise reduction in spectral domain optical coherence tomography retinal images using fuzzification method

机译:使用模糊化方法减少光谱域光学相干断层扫描视网膜图像中的斑点噪声

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In the present work the focus is on speckle noise reduction in Spectral Domain Optical Coherence Tomography (SDOCT) of retinal images using fuzzification technique. OCT in frequency domain is emerging as attractive technique since it simultaneously measures multiple wavelength of reflected light across the spectrum by acquiring volumetric data for the diagnosis of retinal diseases. Even with sophisticated technology SDOCT images has speckle noise and it is about 1–2 μm which degrades the quality of image. In the existing literature, the speckles are denoised by using nonlinear direction preserving digital filters and averaging approaches. In all these methods, there are practical limitations such as loss of detailed resolution, reduction of frame rates and other shortcomings. In this paper, fuzzification method is proposed which uses the maximum fuzzy entropy principle to reduce speckle noise in retinal images. To validate the results SDOCT images were collected from 30 different subjects on 15 different pathological conditions. The results show that the proposed method works well and has enhanced image quality by improving Signal to Noise Ratio (SNR).
机译:在当前的工作中,重点是使用模糊化技术减少视网膜图像光谱域光学相干断层扫描(SDOCT)中的斑点噪声。频域中的OCT成为一种有吸引力的技术,因为它可以通过获取用于诊断视网膜疾病的体积数据同时测量整个光谱范围内反射光的多个波长。即使采用先进的技术,SDOCT图像也具有斑点噪声,并且约为1-2μm,这会降低图像质量。在现有文献中,通过使用非线性方向保持数字滤波器和平均方法来对斑点进行消噪。在所有这些方法中,都存在实际的局限性,例如细节分辨率的损失,帧速率的降低和其他缺点。本文提出了一种模糊化方法,该方法利用最大模糊熵原理来减少视网膜图像中的斑点噪声。为了验证结果,从15个不同病理条件下的30位不同受试者收集了SDOCT图像。结果表明,该方法工作良好,并通过改善信噪比(SNR)提高了图像质量。

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