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Researchers developed a single-image adaptive optics technique for microscopy that uses a phase-diversified multifocal array combined with neural network processing to correct optical aberrations. Unlike traditional methods that require multiple sequential exposures, this approach extracts aberration information from a single frame, with six foci performing optimally. The technique was successfully demonstrated on both calibration bead samples and biological specimens including fixed brain tissue and BPAE cells.
Why it matters
This advancement significantly reduces sample exposure time and speeds up the aberration correction process in multi-photon fluorescence microscopy, which is particularly important for imaging sensitive biological samples that can be damaged by repeated light exposure. The single-frame approach could enable real-time aberration correction in live-cell imaging applications.
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⚠️ Preprint – Noch nicht peer-reviewed
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Abstract: Image-based sensorless adaptive optics is commonly used to improve microscope image quality through aberration compensation. However, its sequential nature leads to repeated sample exposures and a prolonged aberration estimation and correction process. In this work, we used a phase-diversified foci array to enhance the aberration-related information in multi-photon fluorescence microscope images. We showed that, through use of a neural network-based image processing algorithm, we can extract aberration from a single image frame. We discussed how the number of foci can affect the wavefront correction on a bead sample, and we showed that six foci, in general, perform better than two-foci or ten-foci arrangements. We also applied our technique to correct aberrations in biological samples, including a fixed brain tissue and BPAE cells slide.
Source: Single image sensorless adaptive optics using phase-diversified multifocal array