HIGH PERFORMANCE INFORMATIONAL ENVIRONMENT FOR CALCULATIONS IN BIOMEDICINE
https://doi.org/10.20538/1682-0363-2014-4-21-26
Abstract
This work represented one of the possible approaches to providing the required computational resources for solving the complex data processing tasks in biomedicine. The proposed solution is based on four tightly interacted key components of modern high performance computational systems: high performance computational cluster, data processing center, specialized data store and protected telecommunication channels. The examples of tasks, which have been solved in the developed information environment, are given.
About the Authors
K. S. Brazovsky
Siberian State Medical University, Tomsk
Russian Federation
Russian Federation
Ya. S. Pekker
Siberian State Medical University, Tomsk
Russian Federation
Russian Federation
V. P. Dyomkin
National Research Tomsk State University
Russian Federation
Russian Federation
O. S. Umansky
Siberian State Medical University, Tomsk
Russian Federation
Russian Federation
I. V. Tolmachyov
Siberian State Medical University, Tomsk
Russian Federation
Russian Federation
References
1. Duk V., Emanuel V. Information technology in biomedicine research. St. Petersburg, Piter Publ., 2003. 528 p. (in Russian).
2. Fokin V.A., Pekker Ya.S., Berestneva O.G., Gerget O.M. An integral method of evaluation of complex system state. The Bulletin of Tomsk Polytechnic University, 2012, vol. 321, no. 5, pp. 120–124 (in Russian).
3. Bravovsky K.S., Dyomkin V.P., Pekker Ya.S. Three dimensional reconstruction of surface of biological objects using high performance computing. Biotechosphera, 2012, no. 3–4, pp. 60–64 (in Russian).
4. Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J.-C. et al. 3D Slicer as an image computing platform for the quantitative imaging network. Magnetic Resonance Imaging, 2012, vol. 30 (9), pp. 1323–1341. PMID: 22770690.
5. Gleeson P., Crook S., Cannon R.C., Hines M.L., Billings G.O. et al. NeuroML: A language for describing data driven models of neurons and networks with a high degree of bio-logical detail. PLoS Computational biology, 2010, vol. 6. e1000815. doi:10.1371/journal.pcbi.1000815.
6. Delorme A., Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics. Journal of Neuro-science Methods, 2004, vol. 134, pp. 9–21.
7. Pekker Ya.S., Brazovsky K.S. Biological objects modeling in electrical impedance tomography. The Bulletin of Tomsk Polytechnic University, 2004, vol. 307, no. 2 (in Russian).
8. Bibin L., Anquez J., Alcalde J., Boubekeur T., Angelini E., Bloch I. Whole body pregnant woman modeling by digital geometry processing with detailed utero-fetal unit based on medical images. IEEE Transactions on Biomedical Engineering, 2010, vol. 57 (10), pp. 2346–2358.
9.
Review
For citations:
Brazovsky K.S., Pekker Ya.S., Dyomkin V.P., Umansky O.S., Tolmachyov I.V. HIGH PERFORMANCE INFORMATIONAL ENVIRONMENT FOR CALCULATIONS IN BIOMEDICINE. Bulletin of Siberian Medicine. 2014;13(4):21-26. (In Russ.) https://doi.org/10.20538/1682-0363-2014-4-21-26
Views:
703
Email this article 