An intelligent speckle reduction algorithm for optical coherence tomography images

S. Adabi, S. Conforto, Anne Clayton, A. Podoleanu, A. Hojjat, Mohammad R. N. Avanaki
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引用次数: 32

Abstract

Optical Coherence Tomography (OCT) offers three dimensional images of tissue microstructures. Although OCT imaging offers a promising high resolution method, due to the low coherent light source used in the configuration of OCT, OCT images suffers from an artefact called, speckle. Speckle deteriorates the image quality and effects image analysis algorithm such as segmentation and pattern recognition. We present a novel and intelligent speckle reduction algorithm to reduce speckle based on an ensemble framework of Multi-Layer Perceptron (MLP) neural networks. We tested the algorithm on images of retina obtained from a spectrometer-based Fourier-domain OCT system operating at 890 nm, and observed considerable improvement in the signal-to-noise ratio and contrast of the images.
光学相干层析成像的智能散斑减少算法
光学相干断层扫描(OCT)提供组织微观结构的三维图像。尽管OCT成像提供了一种有前途的高分辨率方法,但由于在OCT配置中使用的低相干光源,OCT图像受到称为散斑的人工制品的影响。斑点会降低图像质量,影响图像分割和模式识别等图像分析算法。提出了一种基于多层感知器(MLP)神经网络集成框架的新型智能散斑减少算法。我们在890 nm波长的基于傅立叶域OCT系统的视网膜图像上测试了该算法,并观察到图像的信噪比和对比度有了很大的改善。
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