An Automated Measurement of Ciliary Beating Frequency using a Combined Optical Flow and Peak Detection
An Automated Measurement of Ciliary Beating Frequency using a Combined Optical Flow and Peak Detection
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DOI：
10.4258/hir.2011.17.2.111
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发表时间：
2011-06-01
影响因子：
2.9
通讯作者：
Park, Rae Woong
中科院分区：
文献类型：
--
作者：
Kim, Woojae;Han, Tae Hwa;Park, Rae Woong
目的：粘液纤毛转运系统是呼吸道的主要防御机制。鼻腔中粘液运输的性能可以由纤毛跳动频率（CBF）表示。本研究提出了一种新的方法来测量脑血流利用光流。方法：为了从视频图像中获得CBF的客观估计，开发了一种自动化的基于计算机的图像处理技术。提出了一种基于光流场的图像处理和峰值检测的信号处理方法。我们比较了该方法在图像处理（光流与差分图像）和信号处理（快速傅立叶变换[FFT]与峰值检测[PD]）的各种组合中的测量精度。数字高速录像法结合慢动作录像中的人工计数是脑血流测量的金标准。我们从耳鼻喉科获得了总共50张记录的纤毛鼻窦上皮图像来测量CBF。纤毛鼻窦上皮图像使用电荷耦合器件照相机和倒置显微镜以50-100帧/秒的放大倍数1000记录。结果如下：对于光流（OF）+ PD、OF + FFT、差分图像[DI] + PD和DI + FFT，每种方法的均方误差和方差分别为1.24、0.84 Hz; 11.8、2.63 Hz; 3.22、1.46 Hz和3.82、1.53 Hz。在四种方法中，使用光流的PD显示出最好的性能用于测量鼻粘膜CBF。结论：所提出的方法能够更客观，更有效地测量CBF比目前可能的。
Objectives: The mucociliary transport system is a major defense mechanism of the respiratory tract. The performance of mucous transportation in the nasal cavity can be represented by a ciliary beating frequency (CBF). This study proposes a novel method to measure CBF by using optical flow. Methods: To obtain objective estimates of CBF from video images, an automated computer-based image processing technique is developed. This study proposes a new method based on optical flow for image processing and peak detection for signal processing. We compare the measuring accuracy of the method in various combinations of image processing (optical flow versus difference image) and signal processing (fast Fourier transform [FFT] vs. peak detection [PD]). The digital high-speed video method with a manual count of CBF in slow motion video play, is the gold-standard in CBF measurement. We obtained a total of fifty recorded ciliated sinonasal epithelium images to measure CBF from the Department of Otolaryngology. The ciliated sinonasal epithelium images were recorded at 50-100 frames per second using a charge coupled device camera with an inverted microscope at a magnification of x1,000. Results: The mean square errors and variance for each method were 1.24, 0.84 Hz; 11.8, 2.63 Hz; 3.22, 1.46 Hz; and 3.82, 1.53 Hz for optical flow (OF) + PD, OF + FFT, difference image [DI] + PD, and DI + FFT, respectively. Of the four methods, PD using optical flow showed the best performance for measuring the CBF of nasal mucosa. Conclusions: The proposed method was able to measure CBF more objectively and efficiently than what is currently possible.