Optimized self-adaptive microscopic imaging method and device based on machine learning

Abstract

The invention discloses an optimized self-adaptive microscopic imaging method and device based on machine learning, and the method comprises the following steps: employing ultra-short pulse laser to collect image data through a point scanning method; constructing a convolutional neural network, and inputting image data to the physical model to obtain a simulation result training network; applyingthe training network obtained through training to an adaptive method to optimize an imaging result and eliminate image distortion and acquiring the optimal phase compensation of system and sample distortion correction through a model fitting method. The method can obtain an imaging result with high optimization performance, high image quality and high imaging speed, has the advantages of high speed, high image quality, good expandability and the like, realizes high-speed wavefront distortion compensation based on machine learning, and has a great application prospect in rapid deep tissue imaging of bioscience.

Description

technical field [0001] The present invention relates to the technical field of microscopic imaging, in particular to an optimized self-adaptive microscopic imaging method and device based on machine learning. Background technique [0002] AO (Adaptive Optical, Adaptive Optics) was originally a method applied to astronomical telescopes, and it has been applied to optical microscopes due to its ability to correct the aberrations introduced by optical systems and biological samples. It works by dynamically measuring the distortion accumulated by light in a non-homogeneous sample and correcting for the distortion with active optical elements, thereby restoring diffraction-limited imaging performance deep in scattering tissue. To restore ideal imaging performance, the AO method measures the wavefront distortion present during image formation and corrects the wavefront accordingly to compensate for the inherent distortion of the optical system or sample. There are many AO methods...

AI Technical Summary

Problems solved by technology

However, there are two problems in the existing AO method: 1. When the aberration distortion is larger than the range that the modulator can change, especially under the long-wavelength laser for nonlinear optical imaging, it is often difficult to achieve the optimal AO compensation distortion phase; 2. .The compensation algorithm is complex and the imaging speed is slow

Images