Efficient model-based reconstruction framework for acoustic-resolution optoacoustic microscopy

Acoustic-resolution optoacoustic microscopy (AR-OAM) visualizes internal tissue structures at millimeter to centimeter scale depths with high spatial resolution. The imaging performance mainly depends on the geometry and detection characteristics of the ultrasound transducer. Reconstruction methods incorporating transducer effects are essential to optimize achievable resolution, contrast and overall image quality. Model-based (MB) reconstruction has been shown to provide excellent imaging performance in several optoacoustic embodiments, due to its capacity to accurately model the transducer. However, the applicability of MB reconstruction methods in AR-OAM has been hampered by the high computational cost. Here, we propose an efficient MB reconstruction framework for largescale AR-OAM by considering scanning symmetries, which enabled capitalizing the computational power of a graphics processing unit. The suggested MB reconstruction method is shown to significantly improve the imaging performance of AR-OAM compared to synthetic aperture focusing technique, as validated in in vivo mouse skin experiment.