Traditional optical devices rely on light propagation along a straight path. However, when the light propagates through a blurred medium, its direction get scattered by microscopic particles. This inhomogeneous distortion results in a diffused focus point. Light scattering is one of the main limitations for the optical imaging. This limitation decreases the resolution in depth. Therefore, the ability of focusing light at a desired position has a huge worthwhile for applications of optical imaging. Over the past few years, it was shown that light can be focused inside an object even with strong scattering particles, just by shaping the wavefront of the incident beam. The most successful approaches for light focusing at the presence of scattering objects are feedback-based optical wavefront shaping. In this paper, an iterative feedback-based wavefront shaping is proposed. It uses the genetic algorithm. In summary, we aim to obtain a high intensity in the focus point with fewer steps in iteration while increase the signal-to-noise. The simulations results show that both the above mentioned goals are achieved using the proposed method.

In acoustic-resolution photoacoustic microscopy (AR-PAM) systems, the lateral resolution in the focal zone of the ultrasound (US) transducer is determined by the numerical aperture (NA) of the transducer. To have a high lateral resolution, a large NA is used. However, the larger the NA, the smaller the depth of focus [DOF]. As a result, the lateral resolution is deteriorated at depths out of the focal region. The synthetic aperture focusing technique (SAFT) along with a beamformer can be used to improve the resolution outside the focal region. In this work, for image formation in AR-PAM, we propose the double-stage delay-multiply-and-sum (DS_DMAS) algorithm to be combined with SAFT. The proposed method is evaluated experimentally using hair targets and in vivo vasculature imaging. It is shown that DS_DMAS provides a higher resolution and contrast compared to other methods. For the B-mode images obtained using the hair phantom, the proposed method reduces the average noise level for all the depths by about 134%, 57% and 23%, compared to the original low- resolution, SAFT+DAS and SAFT+DMAS methods, respectively. All the results indicate that the proposed method can be an appropriate algorithm for image formation in AR-PAM systems.