Three-dimensional single-molecule positioning system based on convolutional neural network

Abstract

The invention discloses a three-dimensional single-molecule positioning system based on a convolutional neural network. According to the system, a point spread function is calibrated by using a smallfluorescent ball sample; utilizing the point spread function images and a camera noise model to simulate and excite to generate training samples, and generating a true value three-dimensional matrix corresponding to each training image; inputting the training sample into an unsupervised noise reduction network to obtain noise reduction model parameters; inputting the denoised training sample and the true value three-dimensional matrix into a positioning neural network for training to obtain positioning model parameters; imaging the sample to be observed through a fluorescence microscope, and segmenting the image into the same size as the training set; performing noise reduction on the processed image; inputting the denoised image into the trained positioning network for testing; and finally, performing super-resolution reconstruction on an output result through a sparse coding method to obtain a super-resolution image. The system can maintain high precision and high accuracy of axial positioning for a point spread function excited by high overlapping rate and high density.

Description

technical field [0001] The invention relates to the technical fields of computer vision and computer graphics, in particular to a neural network-based three-dimensional single-molecule positioning system. Background technique [0002] In the field of microscopic imaging, realizing higher-precision 3D imaging is a current frontier issue. Single-molecule localization microscopy can break through the diffraction limit of traditional optical microscopes and greatly improve the positioning accuracy of imaging. It is one of the most important technologies for observing substances inside cells in the biomedical field. In particular, the PSF Engineering method proposed in recent years can effectively improve the axial positioning accuracy of fluorescent molecules through a specially customized point spread function of the optical system, which has attracted extensive attention from scholars in the field. [0003] Most of the current 3D single-molecule localization algorithms have h...

AI Technical Summary

Problems solved by technology

In summary, single-molecule localization microscopy requires a long acquisition process

At the same time, compared with the traditional point spread function, the PSF specially customized for single-molecule positioning often has a higher overlap probability of point spread function and lower signal-to-noise ratio, which greatly limits its wide application.

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