Cell division detection method based on deep learning

A cell division and deep learning technology, applied in the fields of machine vision, deep learning, and cell biology, can solve problems such as inaccurate detection results, low model calculation efficiency, and image changes that do not have translation resistance

Inactive Publication Date: 2016-12-07
SICHUAN UNIV
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Problems solved by technology

[0007] The present invention provides a cell division detection method based on deep learning in view of the deficiencies of the prior art, which solves the problems of difficult design of image features, low model ca...

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  • Cell division detection method based on deep learning
  • Cell division detection method based on deep learning
  • Cell division detection method based on deep learning

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with drawings and embodiments.

[0050] see figure 1 , a cell division detection method based on deep learning, comprising the following steps:

[0051] (1) Obtain images during the cell culture process, and form a continuous image sequence according to the images obtained at a certain time interval; obtain the images during the cell culture process including the following steps:

[0052] (11) Select a kind of animal tissue cells to be cultured, divide them into multiple comparison groups, and culture them in a medium equipped with an electron microscope and a specific culture medium;

[0053] (12) According to the needs of biological experiments, add culture medium that can produce specific stimulation to cells in different groups, observe the changes of cells in a certain period with an electron microscope, and take images according to a certain time interval.

[0054] (2) Biological cytologists an...

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Abstract

The invention discloses a cell division detection method based on deep learning, relates to the technical field including cytobiology and the like, and solves the problem of inaccurate cell division detection results. The cell division detection method comprises the following steps: obtaining an image in a cell culture process, and forming a continuous image sequence according to the images obtained at certain time intervals; judging and comparing all cell division processes in the image sequence, and labelling a position where a process that a paternal cell is divided into two daughter cell membranes can be clearly observed in cell division, and forming a labelled dataset; constructing a full convolutional neural network model, determining the parameter of the full convolutional neural network model, loading the labelled dataset into the full convolutional neural network model, using a deep learning method to directly carry out feature learning on an image sequence, and obtaining the trained full convolutional neural network model; and deploying the trained full convolutional neural network model for automatically detecting the cell division of the cell culture data of a similar type. The cell division detection method is used for cell division detection.

Description

technical field [0001] A cell division detection method based on deep learning is used for cell division detection, involving deep learning, machine vision, cell biology and other technical fields. Background technique [0002] Cell biology is an important research direction of life science. Its purpose is to study the basic life activity rules of cells. The research results are of great significance to cancer treatment, immune regulation, in vitro organ culture and other issues related to human health and life span. The study of cell biology is generally carried out from the aspects of cell functional structure, cell differentiation and proliferation, cell aging and death. As an important research object, cell division has attracted the attention of many researchers. [0003] Traditional cell division detection is mostly done manually, and the personnel who complete the detection work have high background knowledge requirements, and the manual cell division detection work ...

Claims

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Application Information

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IPC IPC(8): G06F19/24
CPCG16B40/00
Inventor 毛华桑永胜陈杰周尧严明
Owner SICHUAN UNIV
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