Istituto di Scienza e Tecnologie dell'Informazione     
Colantonio S., Martinelli M., Salvetti O., Gurevich I. B., Trusova Y. Cell image analysis ontology. In: Pattern Recognition and Image Analysis, vol. 18 (2) pp. 332 - 341. MAIK Nauka/Interperiodica distributed exclusively by Springer Science, 2008.
Cell image analysis in microscopy is the core activity of cytology and cytopathology for assessing cell physiological (cellular structure and function) and pathological properties. Biologists usually make evaluations by visually and qualitatively inspecting microscopic images: this way, they are particularly able to recognize deviations from normality. Nevertheless, automated analysis is strongly preferable for obtaining objective, quantitative, detailed, and reproducible measurements, i.e., features , of cells. Yet, the organization and standardization of the wide domain of features used in cytometry is still a matter of challenging research. In this paper, we present the Cell Image Analysis Ontology (CIAO), which we are developing for structuring the cell image features domain. CIAO is a structured ontology that relates different cell parts or whole cells, microscopic images, and cytometric features. Such an ontology has incalculable value since it could be used for standardizing cell image analysis terminology and features definition. It could also be suitably integrated into the development of tools for supporting biologists and clinicians in their analysis processes and for implementing automated diagnostic systems. Thus, we also present a tool developed for using CIAO in the diagnosis of hematopoietic diseases.
URL: http://www.springerlink.com/content/1054-6618
DOI: 10.1134/S1054661808020211
Subject Image Analysis
Cell Images
I.4.7 Feature Measurement
I.4.8 Scene Analysis
I.2.4 Knowledge Representation Formalisms and Methods
J.3 Life and Medical Sciences. Medical information systems

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