Yi W J, Park K S, Min Y G, Sung M W
Interdisciplinary Program in Medical & Biological Engineering Major, Seoul National University, Korea.
Med Biol Eng Comput. 1997 Nov;35(6):595-9. doi: 10.1007/BF02510966.
Through their rapid periodic actions, the cilia of the human respiratory tract play an important role in clearing inhaled noxious particles. An automated method is developed, based on an image-processing technique, to measure and analyse objectively and quantitatively, ciliary beat frequency (CBF). Microscopic ciliary images are transformed into digitised grey images through an image grabber inside a PC, and signals are extracted from these, based on an image-subtraction algorithm, and are processed through power spectrum analysis using a fast Fourier transform (FFT). By means of the FFT power spectrum, maximum peak frequencies are detected as CBFs in each partitioned block for the entire digitised field. Using these CBFs, distribution maps are composed in various resolutions, showing visually the spatial distribution of CBFs through cells and in a single cell. To measure CBF variations quantitatively, phenylephrine hydrochloride is used, and the changes in CBF influenced by its concentration and duration are observed.
人类呼吸道的纤毛通过其快速的周期性运动,在清除吸入的有害颗粒方面发挥着重要作用。基于图像处理技术开发了一种自动化方法,用于客观、定量地测量和分析纤毛搏动频率(CBF)。微观纤毛图像通过个人计算机内的图像采集器转换为数字化灰度图像,并基于图像减法算法从这些图像中提取信号,然后使用快速傅里叶变换(FFT)通过功率谱分析进行处理。借助FFT功率谱,在整个数字化视野的每个分区块中检测到最大峰值频率作为CBF。利用这些CBF,以各种分辨率组成分布图,直观地显示CBF在细胞间和单个细胞内的空间分布。为了定量测量CBF变化,使用盐酸去氧肾上腺素,并观察其浓度和作用时间对CBF的影响。