改良的小波变换算法在生物微粒检测中的应用(英文)  

Application of Improved Wavelet Transform in Biological Particle Detection

作　　者：章永登[1] 陈良怡[2] 徐涛[1,2] 

机构地区：[1]华中科技大学生命科学与技术学院,分子生物物理教育部重点实验室,武汉430074 [2]中国科学院生物物理研究所,计算与系统生物学中心,北京100101

出　　处：《生物化学与生物物理进展》2010年第10期1144-1150,共7页Progress In Biochemistry and Biophysics

基　　金：supported by grants from National Basic Research Program of China (2006CB705706);The National Natural Science Foundation of China (30871225);Beijing Municipal Science and Technology Commission (5072034)~~

摘　　要：荧光图像的微粒检测已经成为了生物学研究中不可或缺的工具之一.介绍了一种改良的小波变换算法(improved wavelet transform,IWT),该方法实现简单,能够以很高的速度和精度来进行生物微粒的检测.IWT 源自多尺度小波乘积算法(wavelet multiscale products,WMP),但它不仅解决了 WMP算法遇到的问题,而且在处理各类图像的时候具有更强的适应性.使用人工合成的图像和真实的图像来定量地分析 IWT、WMP以及多尺度方差稳定变换算法(multiscale variance stabilizing transform,MSVST)的检测效果.实验结果表明,IWT 在大多数情况下的检测效果比 WMP 好很多,且与更为复杂的MSVST 算法相当.此外,在处理相同图像时,IWT 的速度比 MSVST 快 20%.因此,IWT 算法能够普遍适用于各种生物微粒的自动化检测,其简单准确的特点使之成为荧光图像分析更好的选择.Particle detection of fluorescent images has become an indispensable tool in biological research. Here a simple and fast method for biological particles detection with high efficiency and accuracy, improved wavelet transform （IWT） was introduced.IWT originates from wavelet multiscale products （WMP）. However, it resolves the problems in WMP and is more adaptive in dealing with different types of images. The performance of IWT, WMP and MSVST （multiscale variance stabilizing transform） was quantitatively evaluate by using both synthetic and real fluorescence images. Experimental results show that IWT performs much better than WMP in most cases, and has comparable results with the much complicated algorithm, MSVST. Besides, IWT is 20% faster than MSVST when processing the same images. Therefore, it was concluded that IWT can be generally used for the automatic detection of different kinds of biological particles, and the simplicity and accuracy make it a better choice for fluorescent image analysis.

关 键 词：微粒检测 IWT WMP MSVST 

分 类 号：Q6-33[生物学—生物物理学] Q-334