Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy Cloud Computing Framework

Charalampos Tsirmpas, Kostas Giokas, Dimitra Iliopoulou and Dimitris Koutsouris
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Charalampos Tsirmpas: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, Division of Information Transmission Systems and Material Technology, National Technical University of Athens, Athens, Greece
Kostas Giokas: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, Division of Information Transmission Systems and Material Technology, National Technical University of Athens, Athens, Greece
Dimitra Iliopoulou: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, Division of Information Transmission Systems and Material Technology, National Technical University of Athens, Athens, Greece
Dimitris Koutsouris: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, Division of Information Transmission Systems and Material Technology, National Technical University of Athens, Athens, Greece

International Journal of Reliable and Quality E-Healthcare (IJRQEH), 2012, vol. 1, issue 4, 1-12

Abstract: Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) are two non-invasive techniques that are increasingly being used to identify and quantify biochemical markers associated with certain diseases, e.g., choline in the case of cancer. The associating of MRI/MRS images, patient’s electronic health record, genome information, and environmental factors increase the precision of diagnosis and treatment. The authors present a collaboration framework based on Cloud Computing which allows analysis of MRI/MRS data based on advanced mathematical tools, advanced combination, and link discovery between different data types, so as to increase the precision and consequently avoid non-appropriate therapy and treatment plans.

Date: 2012
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