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作 者:徐昊 周亮 李然[1] 孔平[2] XU Hao;ZHOU Liang;LI Ran;KONG Ping(School of Health Science and Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Jiading District Central Hospital Affiliated Shanghai University of Medicine&Health Sciences,Shanghai 201800,China)
机构地区:[1]上海理工大学健康科学与工程学院,上海200093 [2]上海健康医学院附属嘉定区中心医院,上海201800
出 处:《上海理工大学学报》2022年第1期42-47,共6页Journal of University of Shanghai For Science and Technology
基 金:国家自然科学基金资助项目(11902190,81830052)。
摘 要:为实现激光散斑血流成像设备的便携化,研究了手机散斑衬比血流成像技术。通过分析和重组彩色滤波阵列的光强信号,解决了彩色图像传感器无法获取散斑信号的问题。提出了基于手机相机的散斑衬比分析方法,使用二维离散小波变换对图像低频区域进行增强,并使用kmeans聚类和Ostu算法将背景区域和前景血流区域进行分割和去噪。最后,为验证这两种算法在不同情况下的分割结果,分别进行了血流模拟实验和微循环血流灌注实验。研究结果证明,Ostu算法在不同的血流模型下有更好的分割去噪表现,解决手机自带算法导致血流图像失真问题的同时,提高了图像的可视化效果。In order to realize the portability of laser speckle blood flow imaging equipment,the mobile phone speckle contrast blood flow imaging technology is studied.By analyzing and reorganizing the light intensity signal of the color filter array,the problem that the color image sensor can not obtain the speckle signal is solved.A speckle contrast analysis method based on mobile camera is proposed.The low-frequency region of the image is enhanced by two-dimensional discrete wavelet transform,and the background region and foreground blood flow region are segmented and denoised by K-means clustering and Ostu algorithm.Finally,in order to verify the segmentation results of the two algorithms in different cases,blood flow simulation experiments and microcirculation blood perfusion experiments are carried out respectively.The results show that Ostu algorithm has better segmentation and denoising performance under different blood flow models,solves the problem of blood flow image distortion caused by mobile phone’s own algorithm,and improves the visualization effect of the image.
分 类 号:TN247[电子电信—物理电子学] TP391.4[自动化与计算机技术—计算机应用技术]
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