title: Pattern sorting: a computer-controlled multidimensional sorting method using k-d trees.
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.
authors.affiliation: Department of Genetics, Stanford University School of Medicine, California 94305-5125.
authors.forename: M
authors.initials: M
authors.lastname: Bigos
authors.forename: D R
authors.initials: DR
authors.lastname: Parks
authors.forename: W A
authors.initials: WA
authors.lastname: Moore
authors.forename: L A
authors.initials: LA
authors.lastname: Herzenberg
authors.forename: L A
authors.initials: LA
authors.lastname: Herzenberg
mesh_terms: D016000:Cluster Analysis; D003199:Computer Systems; D003663:Decision Trees; D005434:Flow Cytometry / Q000379:methods*; D010363:Pattern Recognition, Automated