Cell division detection method based on deep learning

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 ...

AI Technical Summary

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 calculation efficiency, inaccurate detection results, low rate of processing a large amount of data, and problems in cell division detection. Image changes do not have the characteristics of anti-translation and other issues

Images