Cell recognition apparatus and method based on phase contrast image and confocal scattering microspectrum

Abstract

The invention provides a cell recognition apparatus based on phase contrast image and confocal scattering microspectrum. The cell recognition apparatus is used for detecting early stage cancerous cells in a sample to be detected, and comprises: a light source illumination unit, which is used for emitting and transmitting light; a phase contrast imaging unit, which comprises a phase contrast microscope and a camera; a confocal spectrum information obtaining unit, which comprises a spectrometer for collecting light which is scattered from the sample to be detected, wherein, the light that irradiates the sample is from the other part of light that penetrates from a coupling lens set and the light scattered from the sample is received and transmitted by the coupling lens set again, and obtaining a spectrum containing the component information of the cells; an image processing and spectral analysis unit, which is used for receiving the phase contrast image and the spectrum, and calculating, analyzing and obtaining a qualitative and a quantitative matching result between cells in the sample to be detected and the normal cells; and a control unit for controlling the light source illumination unit, the phase contrast imaging unit, the confocal spectrum information obtaining unit and the image processing and spectral analysis unit to work normally.

Description

technical field [0001] The invention relates to a device and method for detecting cells, in particular to a cell identification device and method capable of simultaneously obtaining cell morphology and principal components. Background technique [0002] Early cancer detection is a major topic in the medical field. Traditional detection techniques can only detect tumors when they reach a certain size, which often delays the optimal treatment time. If it can be detected when a small amount of cancer changes in the early stage of cells, it will greatly help cancer patients and doctors to detect, intervene and treat early, and improve the survival time and quality of life of cancer patients. [0003] In the process of biological tissue canceration, the shape and structure of cancerous cells are very different from normal cells. These differences are reflected in: the volume of cancer cells is larger than that of normal cells, the nucleus is also significantly enlarged and irreg...

AI Technical Summary

Problems solved by technology

[0004] Medical theory and clinical diagnostic practice and research results show that the gold standard for tumor diagnosis is microscopic observation of pathological sections, but microscopic images only reflect the morphological characteristics of cells. On the other hand, analysis is time-consuming and laborious, and subjective factors such as doctors' clinical experience have a greater impact on the diagnosis

There are some defects in the currently developed detection methods based on optical methods: endoscopic laser confocal microscopy, as a current research hotspot, can only obtain the changes in the three-dimensional morphology of tissue cells, and give qualitative disease analysis, which is different from traditional pathological analysis. In comparison, in vivo, non-invasive, and real-time cell imaging analysis can only be achieved, and the results are still qualitative; spectral analysis technology has unique advantages such as fast, sensitive, and accurate, but current spectral research is aimed at the tissue level, only The average optical properties of the tissue can be obtained, but it does not reach the cell level, so it cannot adapt to the identification and detection of early cancer cells with a small number and no aggregation. At the same time, the signal of a single small cancer cell will be lost in other normal cells, which will inevitably lead to The resolution of the analysis is not high and the specificity is poor

Images