Caenorhabditis elegans identification method and system for easy image segmentation

An image segmentation and recognition method technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of uneven brightness, identification of nematodes, etc., and achieve the effect of good promotion and use value, convenient calculation and filter recognition

Active Publication Date: 2018-03-16
QILU UNIV OF TECH
View PDF2 Cites 1 Cited by
  • 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 so

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Caenorhabditis elegans identification method and system for easy image segmentation
  • Caenorhabditis elegans identification method and system for easy image segmentation
  • Caenorhabditis elegans identification method and system for easy image segmentation

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0047] Example 1:

[0048] The nematode identification method for easy image segmentation of the present invention uses a computer for image collection and image processing to identify nematodes; it includes the following steps:

[0049] (1). Read the experimental image of the nematode on the microplate;

[0050] (2) Calculate the gray-level co-occurrence matrix and contrast characteristic value in the nematode experimental image by means of a sliding window, and obtain the contrast characteristic value centered on each pixel, and transform it into a contrast characteristic image;

[0051] (3) Perform preliminary segmentation of the contrast characteristic image, and identify foreground objects based on the difference in contrast;

[0052] (4) Filter the segmented foreground objects to identify nematodes.

Example Embodiment

[0053] Example 2:

[0054] The nematode identification method for easy image segmentation of the present invention uses a computer for image collection and image processing to identify nematodes; it includes the following steps:

[0055] (1). Read the experimental image of the nematode on the microplate;

[0056] (2) Calculate the gray-level co-occurrence matrix and contrast characteristic value in the experimental image of nematodes through a sliding window, and obtain the contrast characteristic value centered on each pixel, and transform it into the contrast characteristic image;

[0057] (3) Perform preliminary segmentation of the contrast characteristic image, and identify foreground objects based on the difference in contrast;

[0058] (4) Filter the segmented foreground objects to identify nematodes.

[0059] In step (2), each window slides over the covered sub-image, calculates the gray-level co-occurrence matrix and contrast characteristic value in the sub-image area, and assign...

Example Embodiment

[0060] Example 3:

[0061] The nematode identification method for easy image segmentation of the present invention uses a computer for image collection and image processing to identify nematodes; it includes the following steps:

[0062] (1). Read the experimental image of the nematode on the microplate;

[0063] (2) Calculate the gray-level co-occurrence matrix and contrast characteristic value in the experimental image of nematodes through a sliding window, and obtain the contrast characteristic value centered on each pixel, and transform it into the contrast characteristic image;

[0064] (3) Perform preliminary segmentation of the contrast characteristic image, and identify foreground objects based on the difference in contrast;

[0065] (4) Filter the segmented foreground objects to identify nematodes.

[0066] In the step (2), each window slides over the covered sub-image, calculates the gray-level co-occurrence matrix and contrast characteristic value in the sub-image area, and as...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention discloses a Caenorhabditis elegans identification method and system for easy image segmentation, relates to the technical field of biological image processing, and solves the problem that in the prior art, the Caenorhabditis elegans cannot be simply and quickly identified from a Caenorhabditis elegans experimental image with uneven background brightness and a black border. The Caenorhabditis elegans identification method comprises: reading an experimental image of a Caenorhabditis elegans on a microwell plate; calculating a gray co-occurrence matrix and a contrast featurevalue in the Caenorhabditis elegans experimental image in a sliding window manner, obtaining a contrast feature value by taking each pixel as a center, and converting the contrast feature value to generate a contrast feature image; initially segmenting the contrast feature image, and identifying foreground objects according to the contrast difference; and filtering the segmented foreground objects to identify the Caenorhabditis elegans. According to the method and the system disclosed by the present invention, a microwell plate is placed on the rack, and the microwell plate is placed under adigital microscope; the digital microscope is in communication connection with a computer processing control terminal; and the method and the system have the advantages that the Caenorhabditis elegansidentification is simple and the resources occupied are less.

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T7/73G06T7/194
CPCG06T7/194G06T7/73
Inventor 陈维洋李伟伟
Owner QILU UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products