Iranian Journal of Radiology

Published by: Kowsar

Brain Tissue Classification Based on Diffusion Tensor Imaging: A Comparative Study Between Some Clustering Algorithms and Their Effect on Different Diffusion Tensor Imaging Scalar Indices

Ihab Elaff 1 , *
Author Information
1 Computer Engineering Department, Faculty of Engineering, Adnan Menderes University, Aydin, Turkey
Article information
  • Iranian Journal of Radiology: April 01, 2016, 13 (2); e23726
  • Published Online: February 28, 2016
  • Article Type: Research Article
  • Received: October 7, 2014
  • Revised: November 24, 2014
  • Accepted: February 21, 2015
  • DOI: 10.5812/iranjradiol.23726

To Cite: Elaff I. Brain Tissue Classification Based on Diffusion Tensor Imaging: A Comparative Study Between Some Clustering Algorithms and Their Effect on Different Diffusion Tensor Imaging Scalar Indices, Iran J Radiol. 2016 ; 13(2):e23726. doi: 10.5812/iranjradiol.23726.

Abstract
Copyright © 2016, Tehran University of Medical Sciences and Iranian Society of Radiology. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
1. Background
2. Objectives
3. Materials and Methods
4. Results
5. Discussion
Supplements
Acknowledgements
Footnotes
References
  • 1. Kandel ER, Schwartz JH, Jessell TM. Principles of Neural Science. 2000; 4: 1227-46
  • 2. Mortamet B, Zeng D, Gerig G, Prastawa M, Bullitt E. Effects of healthy aging measured by intracranial compartment volumes using a designed MR brain database. Med Image Comput Comput Assist Interv. 2005; 8: 383-91[PubMed]
  • 3. Gur RC, Gunning-Dixon F, Bilker WB, Gur RE. Sex differences in temporo-limbic and frontal brain volumes of healthy adults. Cereb Cortex. 2002; 12(9): 998-1003[PubMed]
  • 4. Sidaros A, Engberg AW, Sidaros K, Liptrot MG, Herning M, Petersen P, et al. Diffusion tensor imaging during recovery from severe traumatic brain injury and relation to clinical outcome: a longitudinal study. Brain. 2008; 131: 559-72[DOI][PubMed]
  • 5. Holtmannspotter M, Peters N, Opherk C, Martin D, Herzog J, Bruckmann H, et al. Diffusion magnetic resonance histograms as a surrogate marker and predictor of disease progression in CADASIL: a two-year follow-up study. Stroke. 2005; 36(12): 2559-65[DOI][PubMed]
  • 6. Albrecht J, Dellani PR, Muller MJ, Schermuly I, Beck M, Stoeter P, et al. Voxel based analyses of diffusion tensor imaging in Fabry disease. J Neurol Neurosurg Psychiatry. 2007; 78(9): 964-9[DOI][PubMed]
  • 7. Concha L, Gross DW, Beaulieu C. Diffusion tensor tractography of the limbic system. AJNR Am J Neuroradiol. 2005; 26(9): 2267-74[PubMed]
  • 8. Bomans M, Hohne KH, Tiede U, Riemer M. 3-D segmentation of MR images of the head for 3-D display. IEEE Trans Med Imaging. 1990; 9(2): 177-83[DOI][PubMed]
  • 9. Westbrook C, Roth CK. MRI in Practice. 2013;
  • 10. Scampini J. Introduction to computed tomography (CT) medical imaging. 2014;
  • 11. Mori S. Introduction to diffusion tensor imaging. 2007;
  • 12. Basser PJ, Mattiello J, LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J. 1994; 66(1): 259-67[DOI]
  • 13. Liu T, Li H, Wong K, Tarokh A, Guo L, Wong ST. Brain tissue segmentation based on DTI data. Neuroimage. 2007; 38(1): 114-23[DOI][PubMed]
  • 14. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B. 1996; 111(3): 209-19[PubMed]
  • 15. Vilanova A, Zhang S, Kindlmann G, Laidlaw D. An introduction to visualization of diffusion tensor imaging and its applications. Visual Process Tensor Fields. 2006; : 121-53
  • 16. Zarei M, Johansen-Berg H, Matthews PM. Diffusion tensor imaging and tractography in clinical neuro sciences. Iran J Radiol. 2003; 1(2): 45-52
  • 17. El-Aff IAI. Extraction of Human Heart Conduction Network from Diffusion Tensor MRI. The 7th IASTED International Conference on Biomedical Engineering. : 217-22
  • 18. Human brain tissues segmentation based on DTI data. 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA). : 876-81
  • 19. Stark DD, Bradley WG. Magnetic Resonance Imaging. 1999;
  • 20. Lufkin RB. The MRI Manual. 1998;
  • 21. Khotanlou H, Colliot O, Atif J, Bloch I. 3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models. Fuzzy Sets Sys. 2009; 160(10): 1457-73
  • 22. Dubey RB, Hanmandlu M, Gupta SK, Gupta SK. The brain MR Image segmentation techniques and use of diagnostic packages. Acad Radiol. 2010; 17(5): 658-71[DOI][PubMed]
  • 23. Portela NM, Cavalcanti GDC, Ren TI. Semi-supervised clustering for MR brain image segmentation. Expert Sys Appl. 2014; 41(4): 1492-7[DOI]
  • 24. Clarke LP, Velthuizen RP, Camacho MA. MRI Segmentation: Methods and Applications. Magnet Reson Imaging. 1995; 13: 343–68
  • 25. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001; 20(1): 45-57[DOI][PubMed]
  • 26. Region Based Hidden Markov Random Field Model for Brain MR Image Segmentation. The Second World Enformatika Conference.
  • 27. Perez P. Markov random fields and images. 1998; : 31
  • 28. Demirkaya O, Asyali MK, Sahoo PK. Image Processing with MATLAB: Application in Medicine and Biology. 2009;
  • 29. Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Sys Man Cyber. 1979; 9: 62-6
  • 30. Wagsta K, Cardie C, Rogers S, Schroedl S. Constrained K-means Clustering with Background Knowledge. Proceedings of the Eighteenth International Conference on Machine Learning. : 577-84
  • 31. Dempster AP, Laird NM, Rubin Maximum DB. Likelihood from Incomplete Data via the EM Algorithm. J R Stat Soc, B. 1977; 39: 1-38
  • 32. Wen Y, He L, von Deneen KM, Lu Y. Brain tissue classification based on DTI using an improved fuzzy C-means algorithm with spatial constraints. Magn Reson Imaging. 2013; 31(9): 1623-30[DOI][PubMed]
Creative Commons License Except where otherwise noted, this work is licensed under Creative Commons Attribution Non Commercial 4.0 International License .
Readers' Comments