An Iterative classification method of 2D CT head data based on statistical and spatial information

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2008, Pages

  Li, Feng ^a   Bartz, Dirk ^b   Gu, Lixu ^a   Audette, Michel ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b UNIVERSITY OF LEIPZIG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION METHODS; CLOSE PROXIMITY; HEAD DATA; MISCLASSIFICATIONS; SPATIAL INFORMATIONS;

PATTERN RECOGNITION; TISSUE;

ITERATIVE METHODS;

EID: 72849141559     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. J. A. Bilmes. A gentle tutorial of the em algorithm and its application to parameter estimation for gaussian mixture and hidden markov models. Technical Report, University of Berkeley, ICSI-TR-97-021, 1998.
2. A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society, Series B, 39(1):1-38, 1977.
3. A. Inselberg and B. Dimsdale. Parallel coordinates: a tool for visualizing multi-dimensionalgeometry. Proc. of IEEE Visualization, 1990.
4. A. Rosenfeld and J. L. Pfaltz. Sequential operations in digital picture processing. J. ACM, 13(4):471-494, 1966.
5. J. A. Sethian. A fast marching level set method for monotonically advancing fronts. Proc. National Academy of Sciences, 93(4):1591-1595, 1996.
6. E. Sifakis, C. Garcia, and G. Tziritas. Bayesian level sets for image segmentation. Visual Communication and Image Representation, 2001.