Multicellular multi-parameter joint estimation and accurate tracking system based on ant colony system

A joint estimation and tracking system technology, applied in the field of cell tracking, can solve the problems of poor generalization, many parameters used, close or crossing, etc., and achieve the effect of precise tracking

Active Publication Date: 2013-08-28
HUAWEI TEHCHNOLOGIES CO LTD
View PDF5 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] 2) Due to the trembling caused by the breathing of the organism, the change of the contrast caused by the cells entering or leaving the confocal plane, the quality of the acquired image is reduced, and the difficulty of cell tracking is increased.
[0006] 3) The number of cells changes with time, and there will be phenomena such as approaching or crossing during movement;
[0009] In recent years, compared with the deterministic cell tracking algorithm, the probabilistic (random) multi-cell tracking technology has developed rapidly. There are two typical technologies. One is that Dr. SMAL proposed a particle filter cell based on the det

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
  • Multicellular multi-parameter joint estimation and accurate tracking system based on ant colony system
  • Multicellular multi-parameter joint estimation and accurate tracking system based on ant colony system
  • Multicellular multi-parameter joint estimation and accurate tracking system based on ant colony system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] The establishment of embodiment 1 ant colony initial distribution

[0073] The initial distribution of the ant colony aims to give the initial distribution of the ant colony in the grayscale image, and its realization is initially through two approaches. For the subsequent cell position estimation module, it is jointly generated by the local gray variance technique and the cell dynamics. For the cell contour estimation module, it is only generated by the local gray variance technique.

[0074] (1) The initial ant colony is generated by the local gray variance technique:

[0075] 1) For any pixel (i, j) of the grayscale image, the intensity I (i,j) It is known that the gray variance of its local area (nearest 8 pixels) is defined as:

[0076] Δ σ ( i , j ) = 1 | N ...

Embodiment 2

[0085] Example 2 Multi-cell position estimation and tracking

[0086] The cell position estimation module aims to redistribute the ant colony initial distribution module (predicted initial ant colony + prior initial ant colony), that is, to form multiple ant colonies, and the corresponding position pheromone field is multimodal. Each ant colony The cluster estimates where a cell exists. Proceed as follows:

[0087] 1) Initialization: the amount of information is given at the position of any pixel (i, j) on the image and the initial diffusion input q ( i , j ) L ( 0 ) = 0 ;

[0088] 2) For the position of the ant at the pixel (i, j), select the next pixel according to the probability, namely P ( i ...

Embodiment 3

[0101] Example 3 Multi-cell position and contour joint tracking

[0102] The cell contour estimation module aims to use the prior initial ant colony distribution. Ants model through ant decision-making according to the local area gray variance. The obtained contour pheromone field is circular, and then estimates the contour of each cell. Proceed as follows:

[0103] 1) Initialization: the amount of information is given at the position of any pixel (i, j) on the image and the initial diffusion input q ( i , j ) C ( 0 ) = 0 ;

[0104] 2) For the position of the ant at the pixel (i, j), select the next pixel according to the probability, namely ( i ′ , j ′ ...

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 invention provides a multicellular multi-parameter joint estimation and accurate tracking system based on an ant colony system, and belongs to the field of cell tracking, wherein parameters include positions, speed, outlines and the like. Initial position distribution of an ant colony is generated due to the fact that a corresponding local area gray level variance of each gray image is defined. Two information pixel fields which work in parallel and are mutually independent are built on the basis, wherein the pixel fields comprise a position field and an outline field. A bounded ant colony decision making system is respectively built on a cell position estimation module and a cell outline estimation module. Finally, important parameters such as positions, speed and outlines of cells are precisely estimated. Therefore, accurate tracking of multiple cells is achieved. By means of mutual cooperation of the bounded heuristic type ant colony systems, a cell detection module is needless, a large number of cell training samples are needless, and the joint estimation and tracking problems of multicellular kinetic parameters and multicellular outlines in a low-contrast cell image sequence are solved.

Description

technical field [0001] The invention provides a multi-cell multi-parameter (position, speed, contour, etc.) joint estimation and precise tracking system based on the ant colony system, which belongs to the field of cell tracking. Background technique [0002] In the past few decades, the rapid development of biological imaging technology has provided a solid technical guarantee for human health. For example, fluorescence microscopy imaging technology has made it possible to study the dynamic behavior of cells. The structure in the cell is marked and tracked, and information such as the speed, acceleration and strength changes of the cell is obtained in the formed cell "life" history record, which is helpful for the research of cell migration and other related cell biology. For example, the neural crest cells of vertebrates will continue to migrate from the dorsal side to the ventral side during the embryonic period. If there is a mutation, the patient's body color, blood cel...

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): G06T7/20G06N3/00
Inventor 徐本连陈庆兰鲁明丽朱培逸毛丽民施健
Owner HUAWEI TEHCHNOLOGIES CO LTD
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap