A Semantic-Based Platform for Medical Image Storage and Sharing Using the Grid

  • Daniela Giordano
  • Carmelo Pino
  • Concetto Spampinato
  • Marco Fargetta
  • Angela Di Stefano
Part of the Communications in Computer and Information Science book series (CCIS, volume 273)


Since the introduction of medical imaging techniques such as MRI, X-Ray, SPECT, PET, large amounts of medical images have been produced in the different fields of medicine. Most of this data is usually stored either in paper format (stored in clinical records) or in optical disks (given to the patients) and this information is partially uncorrelated with the clinical history of patients. Furthermore, the image processing carried out by the physicians that perform the exam and used to make the diagnosis is unknown for other researchers that further treat the same image. In this paper we propose a system that allows radiologists to share medical images (and their processing) and the associated metadata both within the same medical institute and with other medical institutes located anywhere in the world by using GRID services for data (LFC) and metadata (AMGA) storage. The system is also provided with a semantic layer for describing the stored images through a novel RDF schema, which integrates existing ontologies and vocabularies such as FOAF, Mesh and GeneOntology with new terms related to the image processing part. This enables the correlation of medical images with other clinical information and makes our system fully compatible with the existing systems compliant to semantic web standards.


Resource Description Framework Grid Service High Level Feature Simple Object Access Protocol Grid Infrastructure 
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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  1. 1.
    Gabber, E., Fellin, J., Flaster, M., Gu, F., Hillyer, B., Ng, W.T., Özden, B., Shriver, E.A.M.: Starfish: highly-available block storage. In: USENIX Annual Technical Conference, FREENIX Track, pp. 151–163 (2003)Google Scholar
  2. 2.
    Xu, Z., Jiang, H.: Hass: Highly available, scalable and secure distributed data storage systems. In: IEEE International Conference on Computational Science and Engineering, vol. 2, pp. 772–780 (2009)Google Scholar
  3. 3.
    Cheung, K.H., Prud’hommeaux, E., Wang, Y., Stephens, S.: Semantic Web for Health Care and Life Sciences: a review of the state of the art. Brief. Bioinformatics 10, 111–113 (2009)CrossRefGoogle Scholar
  4. 4.
    Freund, J.: Health-e-child: an integrated biomedical platform for grid-based paediatric applications. Stud. Health Technol. Inform. 120, 259–270 (2006)Google Scholar
  5. 5.
    Holford, M.E., Rajeevan, H., Zhao, H., Kidd, K.K., Cheung, K.H.: Semantic Web-based integration of cancer pathways and allele frequency data. Cancer Inform. 8, 19–30 (2009)Google Scholar
  6. 6.
    Diarena, M., Nowak, S., Boire, J.Y., Bloch, V., Donnarieix, D., Fessy, A., Grenier, B., Irrthum, B., Legre, Y., Maigne, L., Salzemann, J., Thiam, C., Spalinger, N., Verhaeghe, N., de Vlieger, P., Breton, V.: HOPE, an open platform for medical data management on the grid. Stud. Health Technol. Inform. 138, 34–48 (2008)Google Scholar
  7. 7.
    Montagnat, J., Breton, V., Magnin, I.: Partitioning medical image databases for content-based queries on a Grid. Methods Inf. Med. 44, 154–160 (2005)Google Scholar
  8. 8.
    Amendolia, S.R., Estrella, F., Hassan, W., Hauer, T., Manset, D., McClatchey, R., Rogulin, D., Solomonides, T.: MammoGrid: A Service Oriented Architecture Based Medical Grid Application. In: Jin, H., Pan, Y., Xiao, N., Sun, J. (eds.) GCC 2004. LNCS, vol. 3251, pp. 939–942. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Giordano, D., Pino, C., Spampinato, C., Fargetta, M., Di Stefano, A.: Nuclear medicine image management system for storage and sharing by using grid services and semantic web. In: Proceedings of the Healthinf 2011: International Conference on Health Informatics, Rome, Italy, January 26-29, 2011 (2010)Google Scholar
  10. 10.
    Broekstra, J., Kampman, A., Harmelen, F.V.: Sesame: An architecture for storing and querying rdf data and schema information. In: Semantics for the WWW. MIT Press (2001)Google Scholar
  11. 11.
    Venugopal, S., Buyya, R., Winton, L.: A grid service broker for scheduling distributed data-oriented applications on global grids. In: MGC 2004: Proceedings of the 2nd Workshop on Middleware for Grid Computing, pp. 75–80. ACM, New York (2004)CrossRefGoogle Scholar
  12. 12.
    Nuno, N.S.: Distributed metadata with the amga metadata catalog. In: Workshop on Next Generation Distributed Data Management - HPDC-15 (2006)Google Scholar
  13. 13.
    Ashburner, M.: Gene ontology: Tool for the unification of biology. Nature Genetics 25, 25–29 (2000)CrossRefGoogle Scholar
  14. 14.
    Soualmia, L., Golbreich, C., Darmoni, S.: Representing the mesh in owl: Towards a semi-automatic migration. In: Proceedings of the KR 2004 Workshop on Formal Biomedical Knowledge Representation, pp. 81–87 (2004)Google Scholar
  15. 15.
    Bieliková, M., Moravcík, M.: Modeling the reusable content of adaptive web-based applications using an ontology. Advances in Semantic Media Adaptation and Personalization, 307–327 (2008)Google Scholar
  16. 16.
    Faro, A., Giordano, D., Spampinato, C., Ullo, S., Di Stefano, A.: Basal Ganglia Activity Measurement by Automatic 3-D Striatum Segmentation in SPECT Images. IEEE Transactions on Instrumentation and Measurement 60(10), 3269–3280 (2011)CrossRefGoogle Scholar
  17. 17.
    Faro, A., Giordano, D., Spampinato, C., Pennisi, M.: Statistical texture analysis of MRI images to classify patients affected by multiple sclerosis. In: 12th Mediterranean Conference on Medical and Biological Engineering and Computing, MEDICON 2010, Porto Carras, Chalkidiki, Greece. International Proceedings of the IFBME, pp. 236–239. Springer, Heidelberg (2010)Google Scholar
  18. 18.
    Giordano, D., Spampinato, C., Scarciofalo, G., Leonardi, R.: An Automatic System for Skeletal Bone Age Measurement by Robust Processing of Carpal and Epiphysial/Metaphysial Bones. IEEE Transactions on Instrumentation and Measurement 59(10), 2539–2553 (2010)CrossRefGoogle Scholar
  19. 19.
    Montagnat, J., Frohner, Á., Jouvenot, D., Pera, C., Kunszt, P., Koblitz, B., Santos, N., Loomis, C., Texier, R., Lingrand, D., Guio, P., Rocha, R.B.D., de Almeida, A.S., Farkas, Z.: A secure grid medical data manager interfaced to the glite middleware. J. Grid Comput. 6, 45–59 (2008)CrossRefGoogle Scholar
  20. 20.
    Giordano, D., Kavasidis, I., Spampinato, C., Bella, R., Pennisi, G., Pennisi, M.: An integrated computer-controlled system for assisting researchers in cortical excitability studies by using transcranial magnetic stimulation. Computer Methods and Programs in Biomedicine, December 14 (2011) ISSN 0169-2607, 10.1016/j.cmpb.2011.10.008Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniela Giordano
    • 1
  • Carmelo Pino
    • 1
  • Concetto Spampinato
    • 1
  • Marco Fargetta
    • 2
  • Angela Di Stefano
    • 3
  1. 1.Department of Electrical, Electronics and Computer EngineeringUniversity of CataniaCataniaItaly
  2. 2.Italian Institute for Nuclear Physics (INFN)CataniaItaly
  3. 3.Institute of Neurological ScienceItalian Research Council (CNR)CataniaItaly

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