Curved chromosome image straightening model generation method, application of model, system, readable storage medium and computer equipment

Abstract

The invention discloses a curving chromosome image straightening model generation method, application of a model, a system, a readable storage medium and computer equipment, and the generation methodcomprises the following steps: obtaining a curving chromosome original image, and processing the curving chromosome original image to obtain a chromosome image; generating a chromosome zoom diagram and a chromosome bending skeleton diagram according to the chromosome diagram; and performing data augmentation on the chromosome zoom diagram and the chromosome bending skeleton diagram, and performingnormalization processing on the augmented chromosome zoom diagram and chromosome bending skeleton diagram to obtain a training data set, and inputting the training data set into a bending chromosomeimage straightening model for training until the model converges. The scheme is based on a deep learning model; chromosome image features are extracted while chromosome detail information is reserved;through a resistance training method, local and global features of an image are self-learned, and a corresponding chromosome map is generated through a skeleton map, so that chromosomes are flexiblystraightened, and a feasible and high-accuracy processing tool is provided for straightening of bent chromosome images.

Description

technical field [0001] The invention relates to the technical field of image processing, and specifically relates to a method for generating a curved chromosome image straightening model based on a BagPix2Pix self-learning model, an application of the model, a system, a readable storage medium, and a computer device. Background technique [0002] With the development of computer technology and artificial intelligence, the recognition and segmentation of images through computer algorithms can be preliminarily realized, and image analysis technology is generally used in medicine for the detection, separation and extraction of objects in medical images. But when the detected object is in different shapes, such as bending and overlapping, graphics algorithms often cannot change the shape of the object at the pixel level. [0003] Human genetic information is carried on chromosomes, so karyotype analysis is the basic method of cytogenetics research, an important means to study th...

AI Technical Summary

Problems solved by technology

This method is suitable for chromosomes with only one large bend, but chromosome photos taken in different experiments and fineness often have three or more bends, so this algorithm often has straightening errors, and cutting and splicing The blanks will also make the chromosome information discontinuous, which is far from meeting the requirements for use

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