AUTOMATED CLASSIFICATION OF NORMAL AND ABNORMAL LEUKOCYTES

The development of an automated system for counting and classifying normal and abnormal leukocytes in peripheral blood smears is described. General requirements are discussed and the results of a simulation experiment are presented. A sample of 1572 leukocytes, divided equally among 17 types, was ph...

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Published inThe journal of histochemistry and cytochemistry Vol. 22; no. 7; pp. 697 - 706
Main Authors BRENNER, J. F, NEURATH, P. W, SELLES, W. D, NECHELES, T. F, GELSEMA, E. S, VASTOLA, E
Format Journal Article
LanguageEnglish
Published London, England Histochemical Soc 01.07.1974
SAGE Publications
Subjects
Autoanalysis
Basophils - cytology
Cell Nucleus
Computers
Eosinophils - cytology
Erythrocytes - cytology
Evaluation Studies as Topic
Histocytochemistry
Humans
Leukocytes - cytology
Lymph - cytology
Lymphocytes - cytology
Methods
Monocytes - cytology
Neutrophils - cytology
Plasma Cells - cytology
Staining and Labeling
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Summary:The development of an automated system for counting and classifying normal and abnormal leukocytes in peripheral blood smears is described. General requirements are discussed and the results of a simulation experiment are presented. A sample of 1572 leukocytes, divided equally among 17 types, was photographed and analyzed using computerized pattern recognition techniques. Various geometrical, color and texture parameters were extracted from the cell images and an optimal set of 20 were used in several computerized classification runs. Training on one-half of the sample and classifying the other half resulted in an over-all correct classification of between 67 and 77% depending on the definition of classification error. When only normal cells are considered, correct classification is obtained for 9l.5% of the cells.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0022-1554
1551-5044
DOI:10.1177/22.7.697