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A Novel Label-Free Pattern Recognition Cytometry Method

A pattern recognition and mark-free technology, applied in instruments, image analysis, computing, etc., can solve problems such as high cost and complex optical path, and achieve the effects of avoiding interference, overcoming complex optical path, and simple installation

Active Publication Date: 2018-03-30
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In terms of sample processing, this method overcomes the shortcomings of traditional flow cytometers that require fluorescent staining, and realizes label-free sample processing; it overcomes the shortcomings of traditional flow cytometers in terms of optical path complexity and high cost; In terms of processing, pattern recognition is innovatively used for automatic classification and recognition of scattering patterns

Method used

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  • A Novel Label-Free Pattern Recognition Cytometry Method
  • A Novel Label-Free Pattern Recognition Cytometry Method
  • A Novel Label-Free Pattern Recognition Cytometry Method

Examples

Experimental program
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Embodiment 1

[0051] Prepare a yeast solution with a suitable concentration, use the device of the present invention to obtain a two-dimensional light scattering pattern of the yeast solution, and compare and verify the experimental results and theoretical simulation results. Figure 2 shows the comparison of the theoretical simulation results of the two-dimensional scattering pattern formed by a single yeast cell in Figure 2(a) and Figure 2(b) with the experimental results in Figure 2(c) and Figure 2(d). Yeast is a single-celled microorganism with a cell diameter of about 3-6 μm. The scatter diagram of the experiment presents two different morphologies as shown in Figure 2(c) and Figure 2(d). In the simulation, yeast cells are assumed to be spherical particles with different diameters, the refractive index is 1.42, the incident wavelength is 532nm, and the refractive index of the surrounding medium is 1.334. The diameter of the cells in Figure 2 (a) is 3.8 μm, and the diameter in (b) is 5.0 ...

Embodiment 2

[0053] Using the device of the present invention, 60 corresponding two-dimensional light scattering patterns of aggregates are obtained from 60 groups of yeast cell aggregates. Among them, 30 groups are patterns of 3 yeast cell aggregations, and the other 30 groups are patterns of 4 yeast cell aggregations. The size of each scatter pattern is 220×220 pixels, and has been normalized, such as Figure 3(a)-Figure 3(d) .

[0054] The present invention uses the AdaBoost method to perform a leave-one-out experiment. The specific implementation steps are: train the light scattering patterns of 59 known classifications (3 yeast cell aggregations or 4 yeast cell aggregations), obtain a group of weak classifiers for pattern recognition, and then use the 60th pattern to weakly classify this The classifier is tested. Record the correct number (CN) of the test data, and calculate the correct rate (AR) through the formula AR=CN / TN. TN represents the number of all 2D light scattering pat...

Embodiment 3

[0058] The device of the invention is used for classifying and identifying normal cervical cells and cancerous cervical cells (HeLa cells). For the classification and identification of cervical cells, a total of 92 two-dimensional light scattering patterns were obtained using the label-free pattern recognition cytometer method of the present invention, 54 of which were normal cervical cell light scattering patterns, and 38 were HeLa cell light scattering patterns. Such as Figure 4(a)-Figure 4(d) shown. When using the AdaBoost method for pattern recognition, 91 scattering patterns are used to train the weak classifier, and the 92nd one is used for testing. As shown in Table 2, the study found that when the number of weak classifier layers is 7, the classification accuracy AR reaches a maximum value of 90.2%, among which the correct rate AR of normal cervical cells is 90.7%, and the correct rate AR of HeLa cells is 89.5%. Normal cervical cells and cancerous cervical cells are...

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Abstract

The invention discloses a novel label-free pattern recognition cytometer method, comprising: preparing a label-free cell solution to be tested and introducing it into a microfluidic channel or making a cell suspension chip; conducting laser light to excite the cells to be tested to form a scattering pattern distributed in a three-dimensional space Light, scattered light passes through the optical imaging system or does not pass through any optical imaging system, is detected by the two-dimensional CMOS detector and obtains the two-dimensional light scattering pattern corresponding to the cell to be tested; the obtained two-dimensional light scattering pattern is transmitted to the pattern recognition classification system, The system automatically learns the two-dimensional light scattering patterns of known cells belonging to different types, and realizes label-free and automatic identification of unknown cells. The recognition result triggers the corresponding device to realize label-free, automated cell counting or cell classification functions. The present invention does not require complicated fluorescent staining of the cells, can automatically and label-free realize the identification, counting and classification of the cells to be tested, is simple and quick to operate, significantly reduces the analysis cost, and has a wide range of applications.

Description

technical field [0001] The invention relates to cell classification and identification, in particular to using a label-free cytometer to obtain light scattering pattern information of cells, and then performing pattern recognition on the light scattering pattern to realize label-free, automatic cell counting or classification functions. Background technique [0002] Traditional flow cytometry can be used for cell analysis and sorting. Generally speaking, traditional flow cytometry requires staining of cells, and fluorescent staining or other biomarkers may have certain effects on cells, especially in the study of the function of living cells. Secondly, the optical path required for fluorescence measurement is complicated, which directly increases the cost of the instrument, and fluorescence measurement requires calibration of the instrument, which is complicated to operate and requires professionals. Finally, in terms of signal processing in the later stage, due to the poss...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/49G06T7/00
Inventor 苏绚涛刘珊珊谯旭
Owner SHANDONG UNIV