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Cell image analysis ontology

  • Information Technologies for Biomedical and Biotechnical Systems
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Abstract

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.

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Authors and Affiliations

  1. Institute of Information Science and Technologies, National Research Council, via G. Moruzzi 1, 56124, Pisa, Italy

    S. Colantonio, M. Martinelli & O. Salvetti

  2. Dorodnicyn Computing Centre, Russian Academy of Sciences, ul. Vavilova 40, Moscow, 119333, Russia

    I. B. Gurevich & Y. O. Trusova

Authors
  1. S. Colantonio
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  2. M. Martinelli
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  3. O. Salvetti
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  4. I. B. Gurevich
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  5. Y. O. Trusova
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Corresponding author

Correspondence to S. Colantonio.

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The text was submitted by the authors in English.

Sara Colantonio. MSc degree with honors in computer science, University of Pisa, 2004; PhD student in information engineering at the Department of Information Engineering, Pisa University; research fellow at the Institute of Information Science and Technologies, National Research Council, Pisa. Received a grant from Finmeccanica for studies in the field of image categorization with applications in medicine and quality control. Her main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. Coauthor of more than 30 scientific papers. Currently involved in a number of European research projects regarding image mining, information technology, and medical decision support systems.

Igor B. Gurevich. Born 1938. Dr. Eng. (Diploma Engineer (Automatic Control and Electrical Engineering), 1961, Moscow Power Engineering Institute, Moscow, USSR); Dr. (Theoretical Computer Science/Mathematical Cybernetics), 1975, Moscow Institute of Physics and Technology, Moscow, USSR. Head of department at the Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow; assistant professor at the Faculty of Computer Science, Moscow State University. Since 1960, has worked as an engineer and researcher in industry, medicine, and universities and in the Russian Academy of Sciences. Area of expertise: image analysis; image understanding; mathematical theory of pattern recognition; theoretical computer science; pattern recognition and image analysis techniques for applications in medicine, nondestructive testing, and process control; knowledge bases; knowledge-based systems. Two monographs (in coauthorship); 135 papers on pattern recognition, image analysis, and theoretical computer science and applications in peer-reviewed international and Russian journals and conference and workshop proceedings; one patent of the USSR and four patents of the RF. Executive secretary of the Russian Association for Pattern Recognition and Image Analysis, member of the governing board of the International Association for Pattern Recognition (representative from the Russian Federation), IAPR fellow. Has served as PI of many research and development projects as part of national research (applied and basic) programs of the Russian Academy of Sciences, the Ministry of Education and Science of the Russian Federation, the Russian Foundation for Basic Research, the Soros Foundation, and INTAS. Deputy editor in chief of Pattern Recognition and Image Analysis.

Massimo Martinelli. Works at the Institute of Information Science and Technologies (ISTI), National Research Council (CNR), Pisa. Member of the W3C multimedia semantics incubator group; coordinator of the CNR-ISTI web systems group. His main interests include semantic web and web technologies. Coauthor of more than 50 scientific papers. Currently involved in a number of European research projects regarding semantic web, information technology, multimedia semantics, and medical decision support systems.

Ovidio Salvetti. Director of research at the Institute of Information Science and Technologies (ISTI), National Research Council (CNR), Pisa. Working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. Coauthor of four books and monographs and more than 300 technical and scientific articles, with ten patents regarding systems and software tools for image processing. Has served as a scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. Member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. Currently the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on Vision and Image Understanding and a member of IEEE and of the steering committee of a number of EU projects. Head of the ISTI Signals and Images Laboratory.

Yulia O. Trusova. Born 1980. Graduated from the Faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University in 2002. Works at the Dorodnicyn Computing Center of the Russian Academy of Sciences. Scientific interests: mathematical theory of pattern recognition and image analysis, methods of discrete mathematics, databases and knowledge bases, and computational linguistics. Coauthor of more than 25 papers. Laureate of the Aspirant Award, 2003–2005. Member of the Russian Association for Pattern Recognition and Image Analysis.

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Colantonio, S., Martinelli, M., Salvetti, O. et al. Cell image analysis ontology. Pattern Recognit. Image Anal. 18, 332–341 (2008). https://doi.org/10.1134/S1054661808020211

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