Method and system for automatically identifying microscopic image of metaphase splitting phase of chromosome

Abstract

The invention discloses an automatic identification method and system for a chromosome metaphase splitting phase microscopic image based on a convolutional neural network. The automatic identification method comprises the following steps: acquiring the chromosome metaphasesplitting phase microscopic image; extracting a chromosome image from the chromosome metaphase splitting phase microscopic image; dividing the extracted chromosome image into a first single independent chromosome image and an adhesion chromosome group image; separating the adhesion chromosome group image into a plurality of second single independent chromosome images; and inputting all the first single independent chromosome images and all the second single independent chromosome images into at least one convolutional neural network model to identify a double centromere chromosome image. The double-centromere chromosome image is identified through the convolutional neural network model, so that automation in the identification process of the double-centromere chromosome is realized.

Description

technical field [0001] The present application relates to the field of radiation biological dosimetry, in particular to a method and system for automatic recognition of microscopic images of chromosome metaphase. Background technique [0002] Chromosomal dicentric analysis (for example, of human peripheral blood lymphocytes) is the most internationally recognized and reliable method for estimating radiation biological dose. [0003] At present, most of the related technologies use manual microscopic reading to identify dicentric chromosomes, which is time-consuming and labor-intensive and is easily affected by human subjectivity. Contents of the invention [0004] In view of the above problems, the present application is proposed in order to provide a method and system for automatic identification of microscopic images of chromosome metaphase that overcome the above problems or at least partially solve the above problems. [0005] According to one aspect of the present in...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the related technologies use the method of manual reading under the microscope to identify dicentric chromosomes. The manual method is time-consuming and labor-intensive and is easily affected by human subjectivity.

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