Liu X Y, Wang W H, Sun Y
Advanced Micro and Nanosystems Laboratory, University of Toronto, 5 King's College Road, Toronto M5S 3G8, Canada.
J Microsc. 2007 Jul;227(Pt 1):15-23. doi: 10.1111/j.1365-2818.2007.01779.x.
Autofocusing is a fundamental procedure towards automated microscopic evaluation of blood smear and pap smear samples for clinical diagnosis. This paper presents comparison results of 16 selected focus algorithms based on 8000 static bright-field images and 1600 dynamic autofocusing trials using 10 blood smear and pap smear samples. Besides static behaviour, dynamic autofocusing performance is introduced for ranking the 16 focus algorithms. The Fibonacci search algorithm is employed for controlling the z-motor of the microscope to reach the focus position that is determined by focus objective functions. Experimental results demonstrate that the variance algorithm provides the best overall performance. Together with our previously reported findings, it is demonstrated that the variance algorithm or the normalized variance algorithm is the optimal focus algorithm for non-fluorescence microscopy applications including pap smear and blood smear imaging.
自动聚焦是临床诊断中对血涂片和巴氏涂片样本进行自动显微镜评估的基本步骤。本文展示了基于8000张静态明场图像和使用10份血涂片及巴氏涂片样本进行的1600次动态自动聚焦试验，对16种选定聚焦算法的比较结果。除了静态行为，还引入了动态自动聚焦性能来对这16种聚焦算法进行排名。采用斐波那契搜索算法控制显微镜的z轴电机，以达到由聚焦目标函数确定的聚焦位置。实验结果表明，方差算法具有最佳的整体性能。结合我们之前报道的研究结果，证明方差算法或归一化方差算法是包括巴氏涂片和血涂片成像在内的非荧光显微镜应用的最佳聚焦算法。
