Abstract
The new results of the research in the field of automation of hemato-poietic 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.
This work was partly supported by the Russian Foundation for Basic Research (grant No. 01-07- 90016, and 03-07-90406) and by Federal Target-Oriented Program “Research and Development in the Priority Directions of Science and Technology” in 2002-2006 (project No. 37.0011.11.0016).
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Keywords
- Chronic Lymphocytic Leukemia
- Lymphoid Tumor
- Cytological Specimen
- Hematopoietic Tumor
- Factor Analysis Approach
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Gurevich, I., Harazishvili, D., Jernova, I., Nefyodov, A., Trykova, A., Vorobjev, I. (2003). Discriminative Power of Lymphoid Cell Features: Factor Analysis Approach. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds) Progress in Pattern Recognition, Speech and Image Analysis. CIARP 2003. Lecture Notes in Computer Science, vol 2905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24586-5_36
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DOI: https://doi.org/10.1007/978-3-540-24586-5_36
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