Biomedical image processing integration through INBIOMED: a web services-based platform

Authors:
David Pérez del Rey;José Crespo;Alberto Anguita;Juan Luis Pérez Ordóñez;Julián Dorado;Gloria Bueno;Vicente Feliú;Antonio Estruch;José Antonio Heredia
Affiliations:
Biomedical Informatics Group, Artificial Intelligence Department, School of Computer Science, Universidad Politécnica de Madrid, Boadilla del Monte, Madrid;Biomedical Informatics Group, Artificial Intelligence Department, School of Computer Science, Universidad Politécnica de Madrid, Boadilla del Monte, Madrid;Biomedical Informatics Group, Artificial Intelligence Department, School of Computer Science, Universidad Politécnica de Madrid, Boadilla del Monte, Madrid;RNASA-IMEDIR (Lab. Redes de Neuronas Artificiales y Sistemas Adaptativos, Centro de Informática Médica y Diagnóstico Radiológico), Universidade da Coruña;RNASA-IMEDIR (Lab. Redes de Neuronas Artificiales y Sistemas Adaptativos, Centro de Informática Médica y Diagnóstico Radiológico), Universidade da Coruña;UCLM-ISA, E.T.S.I. Industriales, Ingeniería de Sistema y Automática, Universidad de Castilla-La Mancha, Ciudad Real;UCLM-ISA, E.T.S.I. Industriales, Ingeniería de Sistema y Automática, Universidad de Castilla-La Mancha, Ciudad Real;Departamento de Tecnología, Universitat Jaume I, Castellón;Departamento de Tecnología, Universitat Jaume I, Castellón
Venue:
ISBMDA'05 Proceedings of the 6th International conference on Biological and Medical Data Analysis
Year:
2005

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Abstract

New biomedical technologies need to be integrated for research on complex diseases. It is necessary to combine and analyze information coming from different sources: genetic-molecular, clinical data and environmental risks. This paper presents the work carried on by the INBIOMED research network within the field of biomedical image analysis. The overall objective is to respond to the growing demand of advanced information processing methods for: developing analysis tools, creating knowledge structure and validating them in pharmacogenetics, epidemiology, molecular and image based diagnosis research environments. All the image processing tools and data are integrated and work within a web services-based application, the so called INBIOMED platform. Finally, several biomedical research labs offered real data and validate the network tools and methods in the most prevalent pathologies: cancer, cardiovascular and neurological. This work provides a unique biomedical information processing platform, open to the incorporation of data coming from other feature disease networks.