Method for classifying multi-parameter data

Measuring and testing – Particle size

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G06F 1546

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active

060149043

ABSTRACT:
A method for automatically classifying multi-parameter data into cluster groups for the purpose of defining different populations of particles in a sample by automatically defining a position of at least one variable position, geometric boundary surface on a two-dimensional scatter plot so as to enclose a group of the displayed particles in a data cluster; with the boundary surface having a polygonal shape defined by a plurality of vertices about at least one cell cluster created by building at least one histogram from cross sections of the two-dimensional scatter plot. Preferably, each cross section of the geometric boundary includes a rectangular, two dimensional gate. The method is particularly useful in the field of cellular analysis using, for example, flow cytometers wherein multi-parameter data is recorded for each cell that passes through an illumination and sensing region. In particular the method is especially useful for classifying and counting immunofluorescently labeled lymphocytes in blood samples from AIDS patients.

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