Continuous gaussian mixture modeling

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

Volumn 1230, Issue , 1997, Pages 176-189

  Aylward, Stephen ^a   Pizer, Stephen ^b  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b Brooks Computer Science Building   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN DISTRIBUTION; INTELLIGENT SYSTEMS; MAGNETIC RESONANCE; MEDICAL PROBLEMS; MONTE CARLO METHODS; SPEECH RECOGNITION;

FALSE POSITIVE RATES; FEATURE VECTORS; FINITE GAUSSIAN MIXTURE MODELS; GAUSSIAN MIXTURE MODEL; GOODNESS OF FIT; HEIGHT RIDGES; NOVEL TECHNIQUES; TRUE POSITIVE RATES;

MEDICAL IMAGING;

EID: 84956865928     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63046-5_14     Document Type: Conference Paper

References (18)

1. Aylward, S.R., "Continuous Mixture Modeling via Goodness-of-Fit Cores," Dissertation, Department of Computer Science, University of North Carolina, Chapel Hill, 1997
2. Aylward, S.R. and Coggins, J.M., "Spatially Invariant Classification of Tissues in MR Images." Visualization in Biomedical Computing, Rochester, MN, 1994
3. Bellegarda, J.R. and Nahamoo, D., "Tied Mixture Continuous Parameter Modeling for Speech Recognition." IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, no. 12. 1990 p. 2033-2045
4. Dawant, B.M., Zijdenbos, A.P. and Margolin, R.A., "Correction of Intensity Variations in MR Images for Computer-Aided Tissue Classification." IEEE Transactions on Medical Imaging, vot. 12, no. 4. 1993 p. 770-781
5. Depmster, A., Laird, N., Rubin, D., "Maximum Likelihood for Incomplete Data via the EM Algorithm." Royal Statistical Society, vol. 1, no. 1. 1977
6. Egan, J.P., Signal detection theory and ROC analysis. Academic Press, Inc., New York, 1975
7. Jordan, M.I. and Xu, L., "Convergence Results for the EM Approach to Mixtures of Experts Architectures." Technical Report, Massachusetts Institute of Technology, Artificial Intelligence Laboratory, November 18, 1994
8. Liang, Z., Jaszezak, R.J. and Coleman, R.E., "Parameter Estimation of Finite Mixtures Using the EM Algorithm and Information Criteria with Application to Medical Image Processing." IEEE Transactions on Nuclear Science, vol. 39, no. 4. 1992 p. 1126-1133
9. McLachlan, G.J. and Basford, K.E., Mixture Models. Marcel Dekker, Inc., New York, vol. 84, 1988 p. 253
10. Meyer, C.R., Bland, P.H. and Pipe, J., "Retrospective Correction of Intensity Inhomogeneities in MRI." IEEE Transactions on Medical Imaging, vol. 14, no. 1. 1995 p. 36-41
11. Morse, B.S., Pizer, S.M., Puff, D.T. and Gu, C., "Zoom-Invariant Vision of Figural Shape: Effects on Cores of Image Disturbances." Computer Vision and Image Understanding, Accepted, 1997
12. Pizer, S.M., Eberly, D., Morse, B.S. and Fritsch, D.S., "Zoom-invariant Vision of Figural Shape: the Mathematics of Cores." Computer Vision and Image Understanding, Accepted, 1997
13. Press, W.H., Flannery, B.P., Teukolsky, S.A. and Vetterling, W.T., Numerical Recipes in C, Cambridge University Press, Cambridge, 1990
14. Read, T.R.C. and Cressie, N.A.C., Goodness-of-fit statistics for discrete multivariate data. Springer-Verlag, New York, 1988
15. Titterington, D.M., Smith, A.G.M. and Markov, U.E., Statistical Analysis of Finite Mixture Distributions, John Wiley and Sons, Chichester, 1985
16. Wells, W.M., III., Grimson, W.E.L., Kikinis, R. and Jolesz, F.A., "Adaptive Segmentation of MRI Data." IEEE Transactions on Medical Imaging, vol. 15, no. 4. 1996 p. 429-442
17. Yoo, T. "Image Geometry Through Multiscale Statistics," Dissertation, Department of Computer Science, University of North Carolina, Chapel Hill, 1996
18. Zhuang, X., Huang, Y., Palaniappan, K. and Zhao, Y., "Gaussian Mixture Density Modeling, Decomposition, and Applications." IEEE Transactions on Image Processing, vol. 5, no. 9. 1996 p. 1293-1302