Partial volume segmentation of cerebral MRI scans with mixture model clustering

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

Volumn 2082, Issue , 2001, Pages 423-430

  Noe, Aljaž ^a   Gee, James C ^b  

^a UNIVERSITY OF LJUBLJANA   (Slovenia)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN MAPPING; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MIXTURES; PROBABILITY DISTRIBUTIONS; TISSUE;

CEREBRAL MRI; IMAGE MODELING; MIXTURE MODEL; MULTI-THREADED IMPLEMENTATION; NEIGHBORHOOD INFORMATION; PARTIAL VOLUME AVERAGING; PARTIAL VOLUME SEGMENTATION; PARTIAL VOLUMES;

CLUSTERING ALGORITHMS;

EID: 84937425495     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45729-1_44     Document Type: Conference Paper

References (14)

1. H. S. Choi, D. R. Haynor, and Y. Kim, Partial volume tissue classification of multichannel magnetic resonance images - a mixel model, in IEEE Transactions on Medical Imaging, vol. 10, pp. 395–407, Sept. 1991.
2. L. Nocera and J. C. Gee, Robust partial volume tissue classification of cerebral MRI scans, in SPIE Medical Imaging (K. M. Hanson, ed.), vol. 3034, pp. 312–322, Feb. 1997.
3. D. H. Laidlaw, K. W. Flescher, and A. H. Barr, Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms, in IEEE Transactions on Medical Imaging, vol. 17, pp. 74–86, Feb. 1998.
4. D. W. Shattuck, S. R. Sandor-Leahy, K. A. Schaper, D. A. Rottenberg, and R. M. Leahy, Magnetic resonance image tissue classification using a partial voume model, 2000. Submitted.
5. J. A. Hartigan, Clustering algorithms. New York: John Wiley & Sons, Inc., 1975.
6. R. O. Duda and P. E. Hart, Pattern classification and scene analysis. New York: John Wiley & Sons, Inc 1973.
7. J. Ashburner and K. Friston, Multimodal image coregistration and partitioning - a unified framework, in Neuroimage, vol. 6, pp. 209–217, Oct. 1997.
8. S. M. Smith, Robust automated brain extraction, in Sixth Int. Conf. on Functional Mapping of the Human Brain, p. 625, 1998.
9. J. G. Sled, A. P. Zijdenbos, and A. C. Evans, A nonparametric method for automatic correction of intensity nonuniformity in MRI data, in IEEE Transactions on Medical Imaging, vol. 17, pp. 87–97, Feb. 1998.
10. http://www.bic.mni.mcgill.ca/brainweb/.
11. R.-S. Kwan, A. Evans, and G. B. Pike, An Extensible MRI Simulator for Post- Processing Evaluation, vol. 1131 of Lecture Notes in Computer Science, pp. 135–140. Springer-Verlag, May 1996.
12. D. L. Collins, A. Zijdenbos, V. Kollokian, J. Sled, N. Kabani, C. Holmes, and A. Evans, Design and construction of a realistic digital brain phantom, in IEEE Transactions on Medical Imaging, vol. 17, pp. 463–468, June 1998.
13. http://neuro-www.mgh.harvard.edu/cma/ibsr.
14. J. C. Rajapakse and F. Kruggel, Segmentation of MR images with intensity inhomogeneities, in Image and Vision Computing, vol. 16, pp. 165–180, 1998.