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Proceedings Paper

High-speed cell classification systems for real-time data classification and cell sorting
Author(s): James F. Leary; James A. Hokanson; Scott R. McLaughlin
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Paper Abstract

When conducting flow cytometric data analyses or cell sorting which results in classification of cells into two or more subpopulations, it is difficult to know which method is providing the best method and further classified using other methods.In this work we describe high-speed cell classification methods suitable for real-time data classification or cell sorting. Real-time generation of statistical classifiers and methods for comparing different classification methods by ROC analysis are also discussed. Multiparameter data mixtures of human MCF-7 breast cancer cells and human bone marrow wee analyzed by several cell classification systems including cluster analyses, principal components and discriminant function analysis. True classifier tags, implemented as additional correlated listmode parameters not used for these analyses, were used to uniquely identify each cell type and to compare classifier results. The performance of classifier systems was also assessed using ROC analysis. Preliminary results are discussed in terms of the advantages/disadvantages and problems/pitfalls of each method.

Paper Details

Date Published: 2 May 1997
PDF: 11 pages
Proc. SPIE 2982, Optical Diagnostics of Biological Fluids and Advanced Techniques in Analytical Cytology, (2 May 1997); doi: 10.1117/12.273634
Show Author Affiliations
James F. Leary, Univ. of Texas Medical Branch/Galveston (United States)
James A. Hokanson, Univ. of Texas Medical Branch/Galveston (United States)
Scott R. McLaughlin, Univ. of Texas Medical Branch/Galveston (United States)


Published in SPIE Proceedings Vol. 2982:
Optical Diagnostics of Biological Fluids and Advanced Techniques in Analytical Cytology
Robert C. Leif; Alexander V. Priezzhev; Toshimitsu Asakura; Robert C. Leif, Editor(s)

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