Method for classifying particles and device for detecting particles

Abstract

The invention discloses a method and a device for classifying particles. The method comprises the following steps: collecting at least two characteristics of the particles which are generated in a detector; forming a distribution scatter diagram of the particles according to the collected particle characteristics; initially dividing the scatter diagram to obtain the distribution of a particle community; determining a core area of the particle community; performing at least one expansion operation on the core area or a profile of the core area; and determining an actual boundary of the scatterdiagram of the particle community according to an expansion result. A final boundary is determined according to morphological characteristics of a scatter diagram core, the size, the shape, the direction and the position of the classification boundary can be adjusted automatically, and the statistical property of the scatter diagram core part is high, so the method and the device can reflect the form of the particle community, and have a strong accuracy and stability.

Description

【Technical field】 [0001] The invention relates to a particle detector, in particular to a particle classification method and a particle detection device for classifying various particles. 【Background technique】 [0002] The particle detector collects two or more features of the particles in the sample, marks these two or more features as two-dimensional or more than two-dimensional vectors, and selects two or three of them Map to a two-dimensional or three-dimensional Cartesian coordinate system, and map all the particles in the sample to the coordinate system to obtain a particle distribution scatter diagram. Under normal circumstances, due to the similarity of the same kind of particles in these characteristics and the differences in these characteristics of different kinds of particles, the same kind of particles form a particle group on the scatter diagram, while different types of particle groups are separated from each other, see figure 1 , the left side is a three-di...

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Problems solved by technology

[0006] In some special cases, different types of particle groups are very close to each other or even overlap to a certain extent, but the centers of each particle group are separated from each other. In this case, the two particle groups are not separated, but have A common boundary, see Figure 4 , the left side is the three-dimensional map, the right side is its two-dimensional projection, the two communities on the right side of the figure overlap, but the core parts of the two communities are separated (the two peaks can be seen to be separated on the three-dimensional map), for In this case, the existing conventional algorithms cannot distinguish these particle swarms very well

For example, the fixed boundary method will have a large error when the cell signal characteristics of some samples are significantly different from the characteristics expressed by the fixed boundary, such as when the particle groups belonging to two categories are very close or overlap Boundary method does not accurately classify particles

Although the center of gravity factor method can automatically adjust the position of the boundary, the size, shape and orientation are still fixed. When the two types of particle communities are close or overlap, this method still cannot accurately classify the particles.

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