A multi-view light sheet microscope image fusion method with improved deconvolution efficiency

Abstract

The invention discloses a multi-view light-sheet microscope image fusion method with improved deconvolution efficiency. The method helps multi-view light-sheet fluorescence microscope image fusion by introducing the concept of virtual view and related convolution algebraic approximation. By calculating the corresponding and add it to the traditional image fusion deconvolution algorithm, so that each deconvolution iterative process contains more information, and is simplified by convolution, without increasing the amount of calculation for each iteration. Reducing the number of deconvolution iterations required with almost constant time. Therefore, the present invention effectively utilizes the mutual information of each view in the multi-view light-sheet fluorescence microscope, and improves the problems of long calculation time and high calculation cost in the process of computer fusion of multi-view light-sheet fluorescence microscope images.

Description

technical field [0001] The invention belongs to the technical field of fluorescence microscopic imaging, and in particular relates to a multi-view light sheet microscope image fusion method with improved deconvolution efficiency. Background technique [0002] Light-sheet fluorescence microscopy (LSFM) is a powerful imaging technique in the biological field, and its application scope extends from single-cell imaging to large-scale tissue imaging. Light-sheet fluorescence microscopy combines the advantages of wide-field microscopy and optical cutting microscopy, and has the advantages of fast three-dimensional imaging, high signal-to-noise ratio, low phototoxicity, and low photobleaching. A light-sheet fluorescence microscope is mainly composed of two optical paths: one is used to generate a very thin light sheet, and the other is used for data acquisition. Light-sheet fluorescence microscopy generates light sheets to excite fluorescence-labeled organisms, and only collects d...

AI Technical Summary

Problems solved by technology

However, these methods generally require many iterations to obtain the desired effect, often requiring a long calculation time

In general, the imaging time of living organisms is long, and the amount of collected data is large (up to Tb level), and the long calculation time limits the application of light-sheet fluorescence microscopy in living imaging.

Images