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GPU-Accelerated Reconstruction of T2 Maps in Magnetic Resonance Imaging Cover

GPU-Accelerated Reconstruction of T2 Maps in Magnetic Resonance Imaging

Measurement Science Review
Volume 15 (2015): Issue 4 (August 2015)
By: Jan Mikulka  
Open Access
|Aug 2015

References

  1. [1] Dvořák, P., Bartušek, K., Smékal, Z. (2014). Unsupervised pathological area extraction using 3D T2 and FLAIR MR images. Measurement Science Review, 14 (2), 357-364.10.2478/msr-2014-0049
    Search in Google Scholar
  2. [2] Mikulka, J., Burget, R., Říha, K., Gescheidtová, E. (2013). Segmentation of brain tumor parts in magnetic resonance images. In 36th International Conference on Telecommunications and Signal Processing, 2-4 July 2013. IEEE, 565-568.10.1109/TSP.2013.6613997
    Search in Google Scholar
  3. [3] Hnilicová, P., Bittšanský, M., Dobrota, D. (2014). Optimization of brain T2 mapping using standard CPMG sequence in a clinical scanner. Measurement Science Review, 14 (2), 117-125.10.2478/msr-2014-0016
    Search in Google Scholar
  4. [4] Hahn, E. (1950) Spin echoes. Physical Review, 80 (4), 580-594.
    Search in Google Scholar
  5. [5] Jiménez, J., Ruiz de Miras, J. (2012). Fast boxcounting algorithm on GPU. Computer Methods and Programs in Biomedicine, 108 (3), 1229-1242.10.1016/j.cmpb.2012.07.00522917763
    Search in Google Scholar
  6. [6] Gogola, D., Krafčík, A., Štrbák, O., Frollo, I. (2013). Magnetic resonance imaging of surgical implants made from weak magnetic materials. Measurement Science Review, 13 (4), 165-168.10.2478/msr-2013-0026
    Search in Google Scholar
  7. [7] Eklund, A., Andersson, M., Knutsson, H. (2012). fMRI analysis on the GPU. Computer Methods and Programs in Biomedicine, 105 (2), 145-161.10.1016/j.cmpb.2011.07.00721862169
    Search in Google Scholar
  8. [8] Zhu, F., Rodriguez-Gonzalez, D., Carpenter, T., Atkinson, M., Wardlaw, J. (2012). Parallel perfusion imaging processing using GPGPU. Computer Methods and Programs in Biomedicine, 108 (3), 1012-1021.10.1016/j.cmpb.2012.06.004377874422824549
    Search in Google Scholar
  9. [9] Broxvall, M., Emilsson, K., Thunberg, P. (2012). Fast GPU based adaptive filtering of 4D echocardiography. IEEE Transactions on Medical Imaging, 31 (6), 1165-1172.10.1109/TMI.2011.217930822167599
    Search in Google Scholar
  10. [10] Prassni, J.S., Ropinski, T., Hinrichs, K. (2010). Uncertainty-aware guided volume segmentation. IEEE Transactions on Visualization and Computer Graphics, 16 (6), 1358-1365.10.1109/TVCG.2010.20820975176
    Search in Google Scholar
  11. [11] Shams, R., Sadeghi, P., Kennedy, R.A., Hartley, R.I. (2010). A survey of medical image registration on multicore and the GPU. IEEE Signal Processing Magazine, 27 (2), 50-60.10.1109/MSP.2009.935387
    Search in Google Scholar
  12. [12] Fluck, O., Vetter, C., Wein, W., Kamen, A., Preim, B., Westermann, R. (2011). A survey of medical image registration on graphics hardware. Computer Methods and Programs in Biomedicine, 104 (3), e45-e57.10.1016/j.cmpb.2010.10.00921112118
    Search in Google Scholar
  13. [13] Pratx, G., Xing, L. (2011) GPU computing in medical physics: A review. Medical Physics, 38 (5), 2011, 2685-2697.10.1118/1.357860521776805
    Search in Google Scholar
  14. [14] Eklund, A. et al. (2013) Medical image processing on the GPU - Past, present and future. Medical Image Analysis, 17 (8), 1073-1094.10.1016/j.media.2013.05.00823906631
    Search in Google Scholar
  15. [15] Giri, S., Chung, Y.C., Merchant, A., Mihai, G., Rajagopalan, S., Raman, S.V., Simonetti, O.P. (2009). T2 quantification for improved detection of myocardial edema. Journal of Cardiovascular Magnetic Resonance, 11 (1), 56.10.1186/1532-429X-11-56280905220042111
    Search in Google Scholar
  16. [16] Jones, C.K. (2003). T2 decay curve acquisition and analysis in MRI noise considerations, short T2, and B1 field encoding. PhD thesis, University of British Columbia.
    Search in Google Scholar
  17. [17] Yoo, Y. (2003). Robust and fast T2 decay analysis for measuring myelin water in MRI. PhD thesis, University of British Columbia.
    Search in Google Scholar
  18. [18] Fraile, R., García-Ortega, E. (2005). Fitting an exponential distribution. Journal of Applied Meteorology and Climatology, 44 (10), 1620-1625.10.1175/JAM2271.1
    Search in Google Scholar
  19. [19] Rektorys, K. (1995). Přehled užite matematiky II. Praha: Prometheus.
    Search in Google Scholar
  20. [20] Prodanov, D. (2009). MRI Processor, v. 1.1.6 22. http://imagejdocu.tudor.lu/doku.php?id=plugin:filter:m ri_processor:start.
    Search in Google Scholar
  21. [21] Starcuk, J., Starcuk, Z., Kozlowski, P. (2008). Marevisi, v. 8.2. More information at: http://www.nrccnrc. gc.ca/eng/solutions/licensing/multidimensional_ mri_data_software.html.
    Search in Google Scholar
  22. [22] Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P. (2007). Numerical Recipes: The Art of Scientific Computing. Cambridge University Press.
    Search in Google Scholar
  23. [23] Lee, V.W., et al. (2010). Debunking the 100X GPU vs. CPU myth: An evaluation of throughput computing on CPU and GPU. In ISCA’10, 19-23 June 2010, Saint- Malo, France
    Search in Google Scholar
DOI: https://doi.org/10.1515/msr-2015-0029 | Journal eISSN: 1335-8871
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Language: English
Page range: 210 - 218
Submitted on: Jan 22, 2015
Accepted on: Aug 12, 2015
Published on: Aug 27, 2015
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
CUDA,
Spin Echo,
T2 relaxation,
magnetic resonance imaging
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2015 Jan Mikulka, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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