Dynamic evaluation of autofocusing for automated microscopic analysis of blood smear and pap smear

Abstract

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.