Evaluation of supervised methods for the classification of major tissues and subcortical structures in multispectral brain magnetic resonance images(468 views)(PDF restricted226 views) Murino L, Granata D, Carfora MF, Selvan SE, Alfano B, Amato U, Larobina M
Comput Med Imag Grap (ISSN: 0895-6111), 2014 Jul; 38(5): 337-347.
Keywords: Atlas-Based, Brain, Denoising, Discriminant Analysis, Segmentation, Subcortical Structures, Histology, Image Segmentation, Magnetic Resonance Imaging, Brain Magnetic Resonance Images, Classification Performance, De-Noising, Discriminant Analysis Methods, False Positive And False Negatives, Supervised Classification, Tissue, Article, False Negative Result, False Positive Result, Functional Neuroimaging, Imaging Phantom, K Nearest Neighbor, Kappa Statistics, Nuclear Magnetic Resonance, Priority Journal, Support Vector Machine, Brain Anatomy, Humans, Magnetic Resonance Imaging Methods,
Affiliations: *** IBB - CNR ***
Istituto per le Applicazioni del Calcolo 'Mauro Picone' CNR, Napoli, Italy
Istituto di Biostrutture e Bioimmagini CNR, Napoli, Italy
Université catholique de Louvain, Department of Mathematical Engineering, Louvain-la-Neuve, Belgium
Universite catholique de Louvain, Department of Mathematical Engineering, Louvain-la-Neuve, Belgium.
Universit catholique de Louvain, Department of Mathematical Engineering, Louvain-la-Neuve, Belgium
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De Jong, L. W., van der Hiele, K., Veer, I. M., Houwing, J. J., Westendorp, R. G., Bollen, E. L., Strongly reduced volumes of putamen and thalamus in Alzheimer's disease: an MRI study (2008) Brain, 131 (PART 12), pp. 3277-3285
Anderson, T. W., (1984) An introduction to multivariate statistical analysis, , Wiley, New York
Magnotta, V. A., Heckel, D., Andreasen, N. C., Cizadlo, T., Corson, P. W., Ehrhardt, J. C., Measurement of brain structures with artificial neural networks: two and three-dimensional applications (1999) Radiology, 211 (3), pp. 781-790
Bazin, P. L., Pham, D., Homeomorphic brain image segmentation with topological and statistical atlases (2008) Med Image Anal, 12 (5), pp. 616-625
Duda, R. O., Hart, P. E., Stork, D. G., (2001) Pattern classification, , John Wiley & Sons, New York
Wand, M. P., Jones, M. C., (1995) Kernel smoothing, , Chapman and Hall, London
Hyv rinen, A., Fast and robust fixed-point algorithms for independent component analysis (1999) IEEE Trans Neural Netw, 10 (3), pp. 626-634
Selvan, S. E., Amato, U., Gallivan, K. A., Qi, C. H., Carfora, M. F., Larobina, M., Descent algorithms on oblique manifold for source-adaptive ICA contrast (2012) IEEE Trans Neural Netw Learn Syst, 23 (12), pp. 1930-1947
Dempster, A. P., Laird, N. M., Rubin, D. B., Maximum likelihood from incomplete data via the EM algorithm (with discussion) (1977) J Roy Stat Soc B, 39, pp. 1-38
Boser, B. E., Guyon, I. M., Vapnik, V. N., A training algorithm for optimal margin classifiers (1992) Proceedings of the 5th annual ACM workshop on computational learning theory, pp. 144-152. , ACM Press, Pittsburgh, PA, D. Haussler (Ed.)
Chang, C. C., Lin, C. J., LIBSVM: a library for support vector machines (2011) ACM Trans Intell Syst Technol, 2 (3). , 27: 1-27: 27
Holmes, C. J., Hoge, R., Collins, L., Woods, R., Toga, A. W., Evans, A. C., Enhancement of MR images using registration for signal averaging (1998) J Comput Assist Tomogr, 22 (2), pp. 324-333
Ahsan, R. L., Allom, R., Gousias, I. S., Habib, H., Turkheimer, F. E., Free, S., Volumes, spatial extents and a probabilistic atlas of the human basal ganglia and thalamus (2007) Neuroimage, 38 (2), pp. 261-270
Woods, R. P., Grafton, S. T., Watson, J. D. G., Sicotte, N. L., Mazziotta, J. C., Automated image registration: II. intersubject validation of linear and nonlinear models (1998) J Comput Assist Tomogr, 22 (1), pp. 153-165
Smith, S. M., Fast robust automated brain extraction (2002) Hum Brain Mapping, 17 (3), pp. 143-155
Evaluation of supervised methods for the classification of major tissues and subcortical structures in multispectral brain magnetic resonance images