Clustering of cell populations in flow cytometry data using a combination of Gaussian mixtures

We propose a supervised learning approach to automatic quantification of cell populations in flow cytometric samples. One sample contains up to millions of measurement vectors with a dimensionality between 10 and 20. Normally, each measurement vector corresponds to a single cell in the biological sa...

Celý popis

Podrobná bibliografia

Vydané v:	Pattern recognition Ročník 60; s. 1029 - 1040
Hlavní autori:	Reiter, Michael, Rota, Paolo, Kleber, Florian, Diem, Markus, Groeneveld-Krentz, Stefanie, Dworzak, Michael
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.12.2016
Predmet:	Acute lymphblastic leukemia Clustering Convex non-negative matrix factorization Flow cytometry Gaussian mixture model L2 distance Flow cytometry L2 distance Convex non-negative matrix factorization Clustering Acute lymphblastic leukemia Gaussian mixture model
ISSN:	0031-3203, 1873-5142
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!