Design and implementation of algorithms for focus automation in digital imaging time-lapse microscopy

Background: Digital time-lapse microscopy using Nomarski-DIC requires that an autofocusing system adapt to changes in cell shape, size, and position while contending with drift, noise, and hysteresis in the microscope and imager. We have designed and implemented an autofocusing system that tracks subjects under dynamic conditions and maintains focus within a threshold of discriminability.

Methods: With the use of proven and novel algorithms for autofocusing in Nomarski, we performed "virtual" experiments on recorded image stacks to simulate drift and sudden displacements and test the search algorithm response.

Results: We found that combining a simple [1, -1] contrast function with an adaptive "warmer-colder" focusing algorithm yields a reasonable compromise between focusing precision and noise tolerance. This method was implemented to record growth kinetics of yeast cells in single and multiple fields of view over several hours.

Conclusions: We have implemented a robust digital autofocus that maintains focus on optically complex samples imaged at high resolution. The tolerance of this system of drift and vibration suggests that it is a practical system for time-lapse imaging in many biological applications.