Cell deformation detection method and system based on deep learning and micro-fluidic chip

Abstract

The invention relates to a cell deformation detection method and system based on deep learning and a micro-fluidic chip. The system comprises the micro-fluidic chip, a constant pressure pump, a microscope, a camera and an electronic device with an image analysis capability, the micro-fluidic chip is used for bearing a cell sample and enabling cells to deform, the constant pressure pump is used for pumping the cell sample into the micro-fluidic chip, the microscope is used for selecting an optimal observation area where cells deform in the micro-fluidic chip, the camera is used for capturing a video image in the cell deformation process, and the electronic device is used for converting video information into an image with time sequence information and analyzing the time sequence information image by using a deep learning algorithm. By means of the system, whole-process image collection of cell deformation can be achieved, the cell deformation capacity is analyzed and detected based on the collected images with time sequence information, and the whole system is simple in structure, low in cost and suitable for application and popularization.

Description

technical field [0001] The invention relates to the technical field of cell detection, in particular to a cell deformation detection method and system based on deep learning and a microfluidic chip. Background technique [0002] Cells are the basic functional units of organisms, maintaining and sensing the physiological environment in organisms through chemical and physical means. Deformability is an important property of cells that plays an important role in embryonic development and homeostasis of human tissues and organs. Some diseases cause changes in the deformability of cells. For example, malaria, sepsis, and Parkinson's disease will reduce the ability of cells to deform, and thyroid cancer and ovarian cancer will increase the ability of cells to deform. Therefore, studying the deformability of cells can provide a deep understanding of the mechanism of disease progression and provide a new way of thinking for detecting and diagnosing diseases, which is of great sign...

AI Technical Summary

Problems solved by technology

[0003] At present, there are some low-throughput methods for detecting cell deformation, such as optical stretcher and microtube sucking technology. These methods can accurately measure the deformation ability of each cell, but the measurement is time-consuming and requires high experimental environment. , cannot be widely used

There is also a high-throughput detection method that does not have high requirements for the experimental environment, but only analyzes a certain moment when the cells deform, resulting in the inability to classify cells with different deformability, poor resolution, and scattered results. There is overlap in the figure

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