A major problem when imaging at depth within a biological sample in confocal or nonlinear microscopy is the introduction of sample induced aberrations. Adaptive optical systems can provide a technique to compensate for these sample aberrations and often iterative optimizations are used to improve on a particular parameter of the image (known as the fitness parameter). In this investigation, using a deformable membrane mirror as the adaptive optic element, we examine the effectiveness of a number of fitness parameters, when used with a genetic algorithm, at determining the optimal mirror shape required to compensate for sample induced aberrations. These fitness parameters are compared in terms of the number of mirror changes required to achieve optimization and the final axial resolution of the optical system. The effect that optimizing each fitness parameter has on the lateral and axial point-spread function is also examined.

© 2008 Optical Society of America

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