TY - CHAP
T1 - Discriminative power of lymphoid cell features
T2 - Factor analysis approach
AU - Gurevich, Igor
AU - Harazishvili, Dmitry
AU - Jemova, Irina
AU - Nefyodov, Alexey
AU - Trykova, Anastasia
AU - Vorobjev, Ivan
PY - 2003
Y1 - 2003
N2 - The new results of the research in the field of automation of hematopoietic tumor diagnostics by analysis of the images of cytological specimens are presented. Factor analysis of numerical diagnostically important features used for the description of lymphoma cell nucleus was carried out in order to evaluate the significance of the features and to reduce the considered feature space. The following results were obtained: a) the proposed features were classified; b) the feature set composed of 47 elements was reduced to 8 informative factors; c) the extracted factors allowed to distinguish some groups of patients. This implies that received factors have substantial medical meaning. The results presented in the paper confirm the advisability of involving factor analysis in the automated system for morphological analysis of the cytological specimens in order to create a complex model of phenomenon investigated.
AB - The new results of the research in the field of automation of hematopoietic tumor diagnostics by analysis of the images of cytological specimens are presented. Factor analysis of numerical diagnostically important features used for the description of lymphoma cell nucleus was carried out in order to evaluate the significance of the features and to reduce the considered feature space. The following results were obtained: a) the proposed features were classified; b) the feature set composed of 47 elements was reduced to 8 informative factors; c) the extracted factors allowed to distinguish some groups of patients. This implies that received factors have substantial medical meaning. The results presented in the paper confirm the advisability of involving factor analysis in the automated system for morphological analysis of the cytological specimens in order to create a complex model of phenomenon investigated.
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U2 - 10.1007/978-3-540-24586-5_36
DO - 10.1007/978-3-540-24586-5_36
M3 - Chapter
AN - SCOPUS:35248840165
SN - 354020590X
SN - 9783540205906
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 298
EP - 305
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Sanfeliu, Alberto
A2 - Ruiz-Shulcloper, Jose
PB - Springer Verlag
ER -