基于双边随机投影算法的光学相干层析成像降噪
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作者单位:

1.江苏理工学院电气信息工程学院生物信息与医药工程研究所,常州 213001;2.常州大学微电子与控制工程学院,常州 213164

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国家自然科学基金(62001196)资助项目;江苏省高校面上项目(17KJB510015)资助项目;江苏省重点研发计划(BE2020648)资助项目。


Noise Reduction of Optical Coherence Tomography Based on Bilateral Random Projection Algorithm
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1.Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001,China;2.School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China

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    摘要:

    为了解决光学相干层析成像(Optical coherence tomography, OCT)系统中的散斑噪声问题,提出了一种基于双边随机投影的光学相干层析成像去噪算法。基于三维OCT图像相邻帧的生物组织结构之间的高度相似性及图像高分辨率的特性,将原始OCT图像信号分解为无噪低秩矩阵、稀疏矩阵以及噪声矩阵;然后采用双边随机投影算法进行求解,提取低秩矩阵,从而去除噪声,恢复无噪图像;在临床数据集上对本文算法进行了测试,并通过信噪比(Signal to noise, SNR)、对比度噪声比(Contrast to noise ratio, CNR)以及等效视数(Equivalent number of looks, ENL)3个指标对降噪效果进行评价。实验结果表明,与稳健性主成分分析算法相比,本文算法在信噪比、对比度信噪比以及等效视数指标上分别提高了1.22 dB、0.84 dB和59.5,能更有效地抑制散斑噪声,且计算复杂度较低。

    Abstract:

    To solve the problem of speckle noise in optical coherence tomography (OCT) system, an optical coherence tomography denoising algorithm based on bilateral random projection is proposed. Based on the high similarity of biological tissue structure between adjacent frames of 3D OCT image and the high resolution of image, the original OCT image signal is decomposed into noiseless low rank matrix, sparse matrix and noise matrix. The bilateral random projection algorithm is then used to solve the problem and extract the low rank matrix, so as to remove the noise and restore the noiseless image. The proposed algorithm is tested on the clinical data set, and the noise reduction effect is evaluated by signal to noise ratio (SNR), contrast to noise ratio (CNR) and equivalent number of looks (ENL). Experimental results show that compared with the robust principal component analysis algorithm, the proposed algorithm improves the SNR, CNR and ENL by 1.22 dB, 0.84 dB and 59.5, respectively. It can suppress speckle noise more effectively and has lower computational complexity.

    表 2 早期青光眼分割无符号表面误差比较Table 2 Comparison of unsigned surface error in early glaucoma layer segmentation
    图1 三维光学相干层析成像示意图Fig.1 Illustration of 3D optical coherence tomography
    图2 算法流程图Fig.2 Flow chart of the proposed algorithm
    图3 OCT图像预处理前后的三维渲染图Fig.3 3D rendering of the OCT image before and after preprocessing
    图4 双边随机投影去噪实验结果Fig.4 Experimental result of bilateral random projection denoising
    图5 一维深度信息信号图Fig.5 One-dimensional depth information signal map
    图6 各算法去噪结果Fig.6 Denoising results of different algorithms
    图1 Framework of identifying similar traffic scenes based on ASVM2LFig.1
    图2 Learning curves of ASVM2L and random-sampling SVM2L on five data setsFig.2
    图3 Change curve of cumulative varianceFig.3
    图4 Feature correlation heat map after dimensionalityreductionFig.4
    图5 Learning curve of ASVM2L on air traffic dataFig.5
    表 1 各算法去噪结果Table 1 Denoising results of different algorithms
    表 3 Table 3 Classification accuracy of traffic scenes
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潘玲佼,范伟伟,吴全玉.基于双边随机投影算法的光学相干层析成像降噪[J].数据采集与处理,2021,36(4):713-721

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  • 收稿日期:2020-09-28
  • 最后修改日期:2020-12-28
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  • 在线发布日期: 2021-07-25