Cell density classification method and device, electronic device and storage medium

A classification method and electronic device technology, applied in the field of computer learning, can solve the time-consuming problems of cell counting and achieve the effect of increasing speed

Pending Publication Date: 2022-05-27
FU TAI HUA IND SHENZHEN +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the existing biological cell counting method is to calculate the number of cells in the image, and calculate the density range of stem cells in the image according to the number of cells, so that the counting of cells will be time-consuming

Method used

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  • Cell density classification method and device, electronic device and storage medium
  • Cell density classification method and device, electronic device and storage medium
  • Cell density classification method and device, electronic device and storage medium

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Experimental program
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Effect test

Embodiment 3

[0070] Embodiment 3 Input the biological cell image to be tested into the training convolutional neural network model until the obtained reconstructed biological cell image matches the biological cell image to be tested, and determine that the cell density of the biological cell image to be tested is the same as the biological cell image to be tested. The density range corresponding to the training convolutional neural network model when reconstructing the biological cell image matching, therefore, in this case, the training convolutional neural network model is used to determine the cell density of the biological cell image to be tested, and the number of cells can be determined without calculating the number of cells. The cell density range is increased, and the speed of the cell count is increased.

[0071] Image 6 This is a flow chart of the cell density classification method provided in the fourth embodiment of the present invention. The cell density classification meth...

Embodiment 4

[0083] Embodiment 4 Acquire multiple training biological cell images divided into multiple different density ranges, and input multiple training biological cell images of each density range into different convolutional neural network models to obtain multiple training convolutional neural network models , input the biological cell image to be tested into the training convolutional neural network model until the obtained reconstructed biological cell image matches the biological cell image to be tested, and determine that the cell density of the biological cell image to be tested is the same as the reconstructed biological cell image. The density range corresponding to the training convolutional neural network model when matching biological cell images. Therefore, in this case, by first training the convolutional neural network model, and then determining the cell density of the biological cell image to be tested according to the training convolutional neural network model, the ...

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Abstract

The invention discloses a cell density classification method, and the method comprises the steps: inputting a to-be-tested biological cell image into a training convolutional neural network model until an obtained reconstructed biological cell image is matched with the to-be-tested biological cell image, and enabling the training convolutional neural network model to correspond to the density range of the cell density of the biological cell image; and determining that the cell density of the to-be-tested biological cell image is a density range corresponding to the training convolutional neural network model when the to-be-tested biological cell image is matched with the reconstructed biological cell image. The invention further provides a cell density classification device, an electronic device and a storage medium, and the cell counting speed can be increased.

Description

technical field [0001] The present invention relates to the technical field of computer learning, and in particular, to a cell density classification method and device, an electronic device and a computer-readable storage medium. Background technique [0002] At present, when studying biological cells, such as biological stem cells, it is often not necessary to know the exact number of stem cells in the image, but only the density range of the stem cells in the image. However, the existing biological cell counting method is to count the number of cells in the image, and calculate the density range of the stem cells in the image according to the number of cells, which will result in time-consuming cell counting. SUMMARY OF THE INVENTION [0003] In view of this, it is necessary to provide a cell density classification method and device, an electronic device and a computer-readable storage medium, which can improve the speed of cell counting. [0004] A first aspect of the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/764G06V10/774G06V20/69G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/24G06F18/214G06V10/774G06V10/82G06V10/776G06V20/698G06V10/761
Inventor 李宛真郭锦斌卢志德
Owner FU TAI HUA IND SHENZHEN
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