Cross chromosome image instance segmentation method based on chromosome trisection feature point positioning

Abstract

The invention discloses a cross chromosome image instance segmentation method based on chromosome trisection feature point positioning, which comprises the following steps of: dividing an image containing chromosomes into S * S grid units, and allocating chromosome instances to a plurality of grid units according to the positions of chromosome instance trisection feature points, wherein each gridunit is responsible for predicting the instance category of one instance. Each output channel is responsible for predicting an instance mask map of a chromosome object to which the grid cell belongs.Compared with an instance positioning segmentation network which only adopts an instance center point to complete instance segmentation, the method provided by the invention adopts chromosome trisection feature points to complete chromosome instance segmentation, has higher segmentation accuracy for crossed and overlapped chromosomes, solves the problems that the segmentation effect of a chromosome image is still not ideal and the chromosomes with small size are easily undetected. Therefore, the robustness of the chromosome instance segmentation algorithm is greatly improved, and the segmentation speed of chromosome instances is increased.

Description

technical field [0001] The present application relates to the field of medical images, in particular to a method for segmenting instances of cross-chromosome images based on the location of chromosome trisection feature points. Background technique [0002] Currently, in a typical karyotype analysis process, it is necessary to perform image processing such as segmentation and classification on chromosome images. Some automatic chromosome analysis systems have been developed in China, but the analysis effect still needs to be improved when the chromosome images overlap and stick together. Traditional segmentation methods include threshold-based on the image histogram, based on morphological erosion and dilation, and based on morphological contour analysis. However, these methods have their limited scope of use, for the shape of the target chromosome and the pattern of overlapping regions. Due to the characteristics of small objects, complex shapes, many adhesions, and diffic...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a cross-chromosome image instance segmentation method based on chromosome trisection feature point positioning, the purpose is to solve the problem that the segmentation effect of chromosome image is still not ideal, and small-volume chromosomes are easy to be missed, and greatly improve the chromosome instance segmentation algorithm Robustness, which speeds up the segmentation of chromosome instances

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