Neighborhood thresholding in mixed model density gating
Abstract:
The present invention provides automatic gating methods that are useful to gate populations of interest in multidimensional data, wherein the populations of interest are only a subset of the populations identifiable in the data. The populations are modeled as a finite mixture of multivariate probability distributions, preferably normal or t distributions. The distribution parameters that provide a best fit of the model distribution to the data are estimated using an Expectation Maximization (EM) algorithm that further includes a dynamic neighborhood thresholding that enables gating of a subset of the clusters present in the data.
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