Importance

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Abstract

An automatic classification method for flow cytometry includes characterizing cells or particles as a vector based on at least two-path optical signals generated when the cells or particles pass through an irradiated area one by one, calculating a distance between the effective cells or particles, in which a shorter distance indicates a higher similarity between the two cells or particles, clustering the cells or particles with high similarity into the same class, continuing to cluster similar cells or particles into the same class until the effective cells or particles are clustered into a number L of classes which should be contained in a sample and is determined based on a measuring principle. This method automatically classifies particles accurately and efficiently.

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First Claim