Method for automatically positioning gene site on gene chip image by using evolutionary algorithm method

Abstract

The invention discloses a method for automatically locating gene points in a gene chip image by using an evolutionary algorithm. Rotate the rotation point of the entire image, use the evolutionary algorithm to find the rotation angle, first perform rotation correction on the gene chip image, and then use the image projection method to perform gene region grid positioning on the gene chip image; (2) gene chip image After the grid positioning of gene regions, all gene regions were extracted, and the evolution algorithm was used in turn to perform grid positioning and output of gene points in the gene region of the gene chip image. The method solves the difficult problem of automatically locating the gene points in the gene chip image.

Description

technical field [0001] The invention belongs to the technical field of biomedical image processing and biomedical instruments, and in particular relates to a method for automatically locating gene points in a gene chip image by using an evolutionary algorithm. Background technique [0002] Gene chip technology has been widely used in disease diagnosis, drug screening and so on. Gene chip image analysis is an important link in the application of gene chip technology. A gene image is generally composed of multiple gene region sub-images, and each gene region is composed of multiple gene points. Generally speaking, gene chip image analysis includes three parts: gene chip image preprocessing, gene point segmentation of gene chip image, and gene point data extraction and analysis. [0003] Microarray images are generally subject to some noise pollution during acquisition and / or scanning. Gene chip image preprocessing is to use filtering method to remove these introduced noises...

AI Technical Summary

Problems solved by technology

[0010] The purpose of the present invention is to provide a method for automatically locating gene points in gene chip images by using an evolutionary algorithm, which solves the problems in the prior art that it is difficult to automatically locate gene points in gene chip images or the positioning accuracy is not good.

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