Pattern sorting: A computer‐controlled multidimensional sorting method using k‐d trees

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Abstract
Multidimensional binary trees provide a memory efficient and general method for computing sorting decisions in real time for a flow cytometer. Their fundamental advantage over conventional lookup table sorting techniques is that sort criteria in the full N‐dimensional data space which cannot be described by projections onto two‐dimensional parameter planes can be effectively implemented. This becomes particularly relevant when multidimensional analysis methods such as principal components or clustering are employed. We describe a prototype implementation of this method and point out other possible implementations.