Parameterization of the distribution of white and grey matter in MRI using the α-stable distribution

Computers in Biology and Medicine

Volumn 43, Issue 5, 2013, Pages 559-567

  Salas Gonzalez, D ^a   Gorriz J M ^a   Ramirez J ^a   Schloegl, M ^b   Lang, E W ^b   Ortiz, A ^c  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF REGENSBURG   (Germany)

^c UNIVERSITY OF MÁLAGA   (Spain)

Author keywords

Stable distribution; Mixture models; MRI segmentation

Indexed keywords

BRAIN SEGMENTATION; GAUSSIAN MIXTURE MODEL; MAGNETIC RESONANCE IMAGING (MRI); METROPOLIS-HASTINGS ALGORITHM; MIXTURE MODEL; MRI SEGMENTATION; SPATIAL INFORMATIONS; STABLE DISTRIBUTIONS;

IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING;

NEUROIMAGING;

ALGORITHM; ARTICLE; GAUSSIAN DISTRIBUTION; GRAY MATTER; METROPOLIS HASTINGS ALGORITHM; NUCLEAR MAGNETIC RESONANCE IMAGING; PARAMETERS; PRIORITY JOURNAL; WHITE MATTER;

ALGORITHMS; BAYES THEOREM; BRAIN; DATABASES, FACTUAL; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84875948977     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2013.01.003     Document Type: Article

References (33)

1. Suetens P., Bellon E., Vandermeulen D., Smet M., Marchal G., Nuyts J., Mortelman L. Image segmentation. methods and applications in diagnostic radiology and nuclear medicine. Eur. J. Radiol. 1993, 17:14-21.
2. Clarke L.R., Velthuizen R.R., Camacho M.A., Heine J.J., Vaidyanathan M., Hall L.O., Thatcher R.W., Silbiger M.L. Mri segmentation. methods and applications. Magn. Resonance Imaging 1995, 13(3):334-368.
3. Pham D.L., Xu C., Prince J.L. Current methods in medical image segmentation. Annu. Rev. Biomed. Eng. 2000, 2(1):315-337.
4. Lim K., Pfefferbaum A. Segmentation of mr brain images into cerebrospinal fluid spaces, white and gray matter. Comput. Assist. Tomogr. 1989, 13:588-593.
5. J. Rogowska, Overview and fundamentals of medical image segmentation, Handbook of Medical Imaging, Academic Press, Inc., Orlando, FL, USA, 2000, pp. 69-85.
6. Balafar M., Ramli A., Saripan M., Mashohor S. Review of brain MRI image segmentation methods. Artif. Intell. Rev. 2010, 33(3):261-274.
7. Laidlaw D.H., Fleischer K.W., Barr A.H. Partial-volume Bayesian classification of material mixtures in mr volume data using voxel histograms. IEEE Trans. Med. Imaging 1998, 17:74-86.
8. Leemput K.V., Maes F., Vandermeulen D., Suetens P. Automated model-based tissue classification of mr images of the brain. IEEE Trans. Med. Imaging 1999, 18(10):897-908.
9. Ruan S., Jaggi C., Xue J., Fadili J., Bloyet D. Brain tissue classification of magnetic resonance images using partial volume modeling. IEEE Trans. Med. Imaging 2000, 19(12):1179-1187.
10. 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.
11. Greenspan H., Ruf A., Goldberger J. Constrained Gaussian mixture model framework for automatic segmentation of mr brain images. IEEE Trans. Med. Imaging 2006, 25(9):1233-1245.
12. da Silva A.R.F. Bayesian mixture models of variable dimension for image segmentation. Comput. Methods Programs Biomed. 2009, 94:1-14.
13. Merisaari H., Parkkola R., Alhoniemi E., Teräs M., Lehtonen L., Haataja L., Lapinleimu H., Nevalainen O.S. Gaussian mixture model-based segmentation of mr images taken from premature infant brains. J. Neurosci. Methods 2009, 182(1):110-122.
14. Ashburner J., Friston K. Unified segmentation. Neuro Image 2005, 26:839-851.
15. Ashburner J., Friston K. Segmentation, Statistical Parametric Mapping 2007, Academic Press, London, pp. 81-91.
16. Nikias C.L., Shao M. Signal Processing with Alpha-Stable Distributions and Applications 1995, Wiley-Interscience, New York.
17. Kuruoglu E., Zerubia J. Skewed alpha-stable distributions for modelling textures. Pattern Recognition Lett. 2003, 24(1-3):339-348.
18. D. Salas-Gonzalez, E.E. Kuruoglu, D.P. Ruiz, Estimation of mixtures of symmetric alpha stable distributions with an unknown number of components, in: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, 2006, ICASSP 2006 Proceedings, Toulouse, France, 2006, pp. 545-548.
19. Salas-Gonzalez D., Kuruoglu E.E., Ruiz D.P. Modelling with mixture of symmetric stable distributions using gibbs sampling. Signal Process. 2010, 90(3):774-783.
20. Salas-Gonzalez D., Kuruoglu E.E., Ruiz D.P. Finite mixture of stable distributions. Digital Signal Process. 2009, 19(2):250-264.
21. D. Salas-Gonzalez, E.E. Kuruoglu, D.P. Ruiz, Bayesian estimation of mixtures of skewed alpha stable distributions with an unknown number of components, in: Proceedings of the 14th European Signal Processing Conference (EUSIPCO 2006), Florence, Italy, 2006.
22. Goldszal A.R., Davatzikos C., Pham D.L., Yan M.X.H., Bryan R.N., Resnick S.M. An image processing system for qualitative and quantitative volumetric analysis of brain images. J. Comput. Assist. Tomogr. 1998, 22(5):827-837.
23. Held K., Kopps E.R., Krause B., Wells W., Kikinis R., Muller-Gartner H. Markov random field segmentation of brain mr images. IEEE Trans. Med. Imaging 1998, 16:878-887.
24. Fischl B., Salat D.H., Busa E., Albert M., Dieterich M., Haselgrove C., van der Kouwe A., Killiany R., Kennedy D., Klaveness S., Montillo A., Makris N., Rosen B., Dale A.M. Whole brain segmentation. automated labeling of neuroanatomical structures in the human brain. Neuron 2002, 33(3):341-355.
25. Liao S., Chung A.C.S. Feature based nonrigid brain mr image registration with symmetric alpha stable filters. IEEE Trans. Med. Imaging 2010, 29(1):106-119.
26. Nolan J.P. Numerical calculation of stable densities and distribution functions. Commun. Stat. Stochastic Models 1997, 13(4):759-774.
27. V.M. Zolotarev, One dimensional stable distributions, Translation on Mathematical Monographs 65. American Mathematical Society, Providence, 1986.
28. Diebolt J., Robert C.P. Estimation of finite mixture distributions through Bayesian sampling. J. R. Stat. Soc. Ser. B 1994, 56(2):363-375.
29. Richardson S., Green P.J. On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. R. Stat. Soc.. Ser. B (Methodological) 1997, 59(4):731-792.
30. Segovia F., Górriz J.M., Ramírez J., Salas-Gonzalez D., Álvarez I., López M., Chaves R., Padilla P. Classification of functional brain images using a GMM-based multi-variate approach. Neurosci. Lett. 2010, 474(1):58-62.
31. Górriz J.M., Lassl A., Ramírez J., Salas-Gonzalez D., Puntonet C.G., Lang E.W. Automatic selection of rois in functional imaging using Gaussian mixture models. Neurosci. Lett. 2009, 460(2):108-111.
32. Kennedy D.N., Filipek P.A., Caviness V.S. Anatomic segmentation and volumetric calculations in nuclear magnetic resonance imaging. IEEE Trans. Med. Imaging 1989, 8:1-7.
33. Filipek P.A., Richelme C., Kennedy D.N., Caviness V.S. The young adult human brain: an mri-based morphometric analysis. Cereb. Cortex. 1994, 4(4):344-360.