FAST-PVE: Extremely fast Markov random field based brain MRI tissue classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7944 LNCS, Issue , 2013, Pages 266-276

  Tohka, Jussi ^a  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

brain imaging; magnetic resonance imaging; Segmentation

Indexed keywords

BRAIN IMAGING; BRAIN MAGNETIC RESONANCE IMAGES; MARKOV RANDOM FIELDS; QUANTITATIVE ACCURACY; SEGMENTATION METHODS; SEGMENTATION RESULTS; STATE-OF-ART METHODS; TISSUE CLASSIFICATION;

ALGORITHMS; IMAGE ANALYSIS; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MARKOV PROCESSES; NEUROIMAGING;

TISSUE;

EID: 84884476464     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38886-6_26     Document Type: Conference Paper

References (23)

1. Dale, A., Fischl, B., Sereno, M.: Cortical surface-based analysis. I. segmentation and surface reconstruction. Neuroimage 9, 179-194 (1999)
2. Ashburner, J., Friston, K.J.: Voxel-based morphometry-the methods. Neuroimage 11(6 pt. 1), 805-821 (2000)
3. Tohka, J., Dinov, I.D., Shattuck, D.W., Toga, A.W.: Brain MRI tissue classification based on local Markov random fields. Magn. Reson. Imaging 28(4), 557-573 (2010)
4. Van Leemput, K., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based tissue classification of MR images of the brain. IEEE Trans. Med. Imaging 18(10), 897-908 (1999)
5. Shattuck, D.W., Sandor-Leahy, S.R., Schaper, K.A., Rottenberg, D.A., Leahy, R.M.: Magnetic resonance image tissue classification using a partial volume model. Neuroimage 13(5), 856-876 (2001)
6. Zhang, Y., Brady, M., Smith, S.: Segmentation of brain mr images through a hidden random markov field model and the expectation-maximization algorithm. IEEE Trans. Med. Imaging 20(1), 45-57 (2001)
7. Tohka, J., Zijdenbos, A., Evans, A.: Fast and robust parameter estimation for statistical partial volume models in brain MRI. Neuroimage 23(1), 84-97 (2004)
8. Evans, A.C.: Large-scale morphometric analysis of neuroanatomy and neuropathology. Anat. Embryol (Berl) 210(5-6), 439-446 (2005)
9. Bellec, P., Carbonell, F.M., Perlbarg, V., Lepage, C., Lyttelton, O., Fonov, V., Janke, A., Tohka, J., Evans, A.C.: A neuroimaging analysis kit for matlab and octave. In: Proceedings of the 17th International Conference on Functional Mapping of the Human Brain (2011)
10. Gaser, C.: VBM8 toolbox, http://dbm.neuro.uni-jena.de/vbm/
11. Koo, J., Evans, A., Gross, W.: 3-D brain tissue classification on FPGAs. IEEE Trans. Image Proc. 18, 2735-2746 (2009)
12. Li, S.: Markov Random Field Modeling in Image Analysis. Springer, London (2009)
13. Santago, P., Gage, H.D.: Quantification of MR brain images by mixture density and partial volume modeling. IEEE Trans. Med. Imaging 12(3), 566-574 (1993)
14. Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes, 3rd edn. The Art of Scientific Computing. Cambridge University Press (2007)
15. Rousseeuw, P.J., Leroy, A.M.: Robust Regression and Outlier Detection. Wiley-Interscience, New York (1987)
16. Manjon, J., Tohka, J., Garcia-Marti, G., Carbonell-Caballero, J., Lull, J., Marti-Bonmati, L., Robles, M.: Robust MRI brain tissue parameter estimation by multistage outlier detection. Magn. Reson. Med. 59, 866-873 (2008)
17. Wang, Y., Adah, T., Xuan, J., Szabo, Z.: Magnetic resonance image analysis by information theoretic criteria and stochastic site models. IEEE Trans. Inform. Tech. Biomed. 5(2), 150-158 (2001)
18. Besag, J.: On the statistical analysis of dirty pictures. J. R. Stat. Soc. Ser. B 48(3), 259-302 (1986)
19. Szeliski, R., Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., Rother, C.: A comparative study of energy minimization methods for markov random fields with smoothness-based priors. IEEE Trans. Patt. Analysis Mach. Intell. 30, 1068-1080 (2008)
20. Huang, F., Narayan, S., Wilson, D., Johnson, D., Zhang, G.Q.: A fast iterated conditional modes algorithm for water-fat decomposition in mri. IEEE Trans. Med. Imaging 30, 1480-1492 (2011)
21. Collins, L., Zijdenbos, A., Kollokian, V., Sled, J., Kabani, N., Holmes, C., Evans, A.: Design and construction of a realistic digital brain phantom. IEEE Trans. Med. Imaging 17(3), 463-468 (1998)
22. Kwan, R.S., Evans, A., Pike, G.: MRI simulation-based evaluation of image-processing and classification methods. IEEE Trans. Med. Imag. 18(11), 1085-1097 (1999)
23. Manjon, J.V., Tohka, J., Robles, M.: Improved estimates of partial volume coefficients from noisy brain MRI using spatial context. Neuroimage 53(2), 480-490 (2010)