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Nematode identification method and system for easy image segmentation

A recognition method and image segmentation technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as uneven brightness, identifying nematodes, etc., and achieve good promotion and use value, convenient calculation and filter recognition effects

Active Publication Date: 2021-06-22
QILU UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical task of the present invention is to address the above deficiencies, provide a nematode identification method and system that is easy to image segmentation, and solve the problem that nematodes cannot be easily and quickly identified from nematode experimental images with uneven background brightness and black borders in the prior art question

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  • Nematode identification method and system for easy image segmentation
  • Nematode identification method and system for easy image segmentation
  • Nematode identification method and system for easy image segmentation

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Embodiment 1

[0048] The nematode identification method that is easy to image segmentation of the present invention utilizes computer to carry out image acquisition and image processing and identify nematode; comprises the following steps:

[0049] (1), read in the experimental image of the nematode on the microwell plate;

[0050] (2) Calculate the gray level co-occurrence matrix and contrast eigenvalues ​​by means of a sliding window in the nematode experimental image, and obtain the contrast eigenvalues ​​centered on each pixel, and convert to generate contrast eigenimages;

[0051] (3) Preliminarily segment the contrast characteristic image, and identify the foreground object according to the contrast difference;

[0052] (4) Filtering the above-mentioned segmented foreground objects to identify nematodes.

Embodiment 2

[0054] The nematode identification method that is easy to image segmentation of the present invention utilizes computer to carry out image acquisition and image processing and identify nematode; comprises the following steps:

[0055] (1), read in the experimental image of the nematode on the microwell plate;

[0056](2) Calculate the gray level co-occurrence matrix and contrast eigenvalues ​​by means of a sliding window in the nematode experimental image, and obtain the contrast eigenvalues ​​centered on each pixel, and convert to generate contrast eigenimages;

[0057] (3) Preliminarily segment the contrast characteristic image, and identify the foreground object according to the contrast difference;

[0058] (4) Filtering the above-mentioned segmented foreground objects to identify nematodes.

[0059] In step (2), each window slides over the covered sub-image, calculates the gray-scale co-occurrence matrix and contrast eigenvalue in the sub-image area, and assigns the cont...

Embodiment 3

[0061] The nematode identification method that is easy to image segmentation of the present invention utilizes computer to carry out image acquisition and image processing and identify nematode; comprises the following steps:

[0062] (1), read in the experimental image of the nematode on the microwell plate;

[0063] (2) Calculate the gray level co-occurrence matrix and contrast eigenvalues ​​by means of a sliding window in the nematode experimental image, and obtain the contrast eigenvalues ​​centered on each pixel, and convert to generate contrast eigenimages;

[0064] (3) Preliminarily segment the contrast characteristic image, and identify the foreground object according to the contrast difference;

[0065] (4) Filtering the above-mentioned segmented foreground objects to identify nematodes.

[0066] In the step (2), each window slides over the sub-image formed by covering, calculates the gray-level co-occurrence matrix and the contrast feature value in the sub-image are...

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Abstract

The invention discloses a method and system for nematode identification that is easy to image segmentation, relates to the technical field of biological image processing, and solves the problem that nematodes cannot be easily and quickly identified from nematode experimental images with uneven background brightness and black borders in the prior art. The nematode identification method includes: reading in the experimental image of the nematode on the microporous plate; calculating the gray-scale co-occurrence matrix and the contrast feature value in the nematode experimental image through a sliding window, and obtaining the contrast feature centered on each pixel value, and converted to generate a contrast feature image; the contrast feature image is initially segmented, and the foreground object is identified according to the contrast difference; the above-mentioned segmented foreground object is filtered to identify the nematode; the microplate is placed on the rack, In addition, the micro-orifice plate is placed under the digital microscope, and the digital microscope is connected with the computer processing control terminal through communication; it has the advantages of simple identification of nematodes and less resource occupation.

Description

technical field [0001] The invention relates to the technical field of biological image processing, in particular to a nematode identification method and system which are easy to image segmentation. Background technique [0002] In the field of biological image processing technology, Caenorhabditis elegans (Caenorhabditis elegans) is a model animal with many applications. It is small in size, about 1 mm in length, and easy to cultivate. Common Caenorhabditis elegans has an average lifespan of about two to three weeks and a developmental time of about three days in a culture environment at 20°C in the laboratory. In 1974 Brenner chose to use C. elegans as a model organism to study developmental and neuroscience issues. Image acquisition and image processing are used in many high-throughput screening efforts using C. elegans. The image data produced in high-throughput screening experiments far exceeds the ability of manual inspection and analysis, making researchers resort t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/73G06T7/194
CPCG06T7/194G06T7/73
Inventor 陈维洋李伟伟
Owner QILU UNIV OF TECH