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6th ESACP Congress, Heidelberg, April 7-11, 1999 |
A127
The automatic sorting of nuclei populations for DNA analysis of solid tumors
can be obtained by the Principal Component Analysis of 38 parameters,
measured or calculated on each nucleus (cf Part I). The use of so many
paramaters may not be justified, and could alter the quality of the analysis.
So, in order to improve the classification method, parameters have been
arranged according to their degree of importance, by using two different
approaches : the Knock Out method (*) and the critical analysis of
parameters, taken one by one during the Principal Component Analysis
(looking for redundant parameters, aberrantly distributed parameters and
parameters notably implied only in high rank components). The results
obtained by the two approaches are in accordance with each other and put in
light 19 out of 38 pertinent parameters.
MULTIPARAMETRIC CELL SORTING FOR DNA MEASUREMENT OF SOLID TUMORS.
PART II : SELECTION OF THE MOST INFORMATIVE PARAMETERS.
Signolle JP 1, Herlin P 2, Plancoulaine B 1, Masson E 3,
Elmoataz A 3, Lefranc F 3, Boudry C 4, Hémery A 1, Bloyet D 3
1) Départment Mesures Physiques IUT Caen,
2) Laboratoire d'Anatomie Pathologique, Centre de Lutte Contre le Cancer
François Baclesse, Caen,
3) Greyc - ISMRA, UPRES-A CNRS 6072, Caen,
4) Lermat - ISMRA, UPRES-A CNRS 6004, Caen,
1-4) Pôle Traitement et Analyse d'Images de Basse Normandie, France
* Goresnic A, Rotman SR: Texture classification using the cortex transform.
Graphical Models and Image Processing 54:329-392(1992)