A Novel Rotationally Invariant Region-Based Hidden Markov Model for Efficient 3-D Image Segmentation
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Roger C. Tam | Rafeef Abugharbieh | Albert Huang | R. Abugharbieh | R. Tam | A. Huang | Albert Huang
[1] L. Baum,et al. A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .
[2] L. Baum,et al. An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process , 1972 .
[3] Albert Huang,et al. Image Segmentation Using an Efficient Rotationally Invariant 3 D Region-Based Hidden Markov Model , 2008 .
[4] D. A. Bell,et al. Information Theory and Reliable Communication , 1969 .
[5] Amir Averbuch,et al. A region-based MRF model for unsupervised segmentation of moving objects in image sequences , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[6] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[7] Sean R. Eddy,et al. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids , 1998 .
[8] J. Besag. On the Statistical Analysis of Dirty Pictures , 1986 .
[9] J. Baker,et al. The DRAGON system--An overview , 1975 .
[10] Stephen M. Smith,et al. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.
[11] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[12] H. Gudbjartsson,et al. The rician distribution of noisy mri data , 1995, Magnetic resonance in medicine.
[13] Qionghai Dai,et al. Region-based hidden Markov models for image categorization and retrieval , 2007, Electronic Imaging.
[14] Gerhard Rigoll,et al. Facial Expression Recognition with Pseudo-3D Hidden Markov Models , 2001, DAGM-Symposium.
[15] Biing-Hwang Juang,et al. Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.
[16] Stan Z. Li,et al. Markov Random Field Models in Computer Vision , 1994, ECCV.
[17] James Ze Wang,et al. A computationally efficient approach to the estimation of two- and three-dimensional hidden Markov models , 2006, IEEE Transactions on Image Processing.
[18] Paolo Frasconi,et al. Hidden Tree Markov Models for Document Image Classification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[19] M. Ibrahim,et al. Hidden Markov models-based 3D MRI brain segmentation , 2006, Image Vis. Comput..
[20] Olivier Cappé,et al. Ten years of HMMs , 2001 .
[21] Jr. G. Forney,et al. Viterbi Algorithm , 1973, Encyclopedia of Machine Learning.
[22] George Kuczera,et al. A general Bayesian framework for calibrating and evaluating stochastic models of annual multi-site hydrological data , 2007 .
[23] John S. Boreczky,et al. A hidden Markov model framework for video segmentation using audio and image features , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[24] S. Beucher,et al. Watersheds of functions and picture segmentation , 1982, ICASSP.
[25] Jin-Hyung Kim,et al. An HMM-Based Threshold Model Approach for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[26] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[27] Haikady N. Nagaraja,et al. Inference in Hidden Markov Models , 2006, Technometrics.
[28] Roberto Pieraccini,et al. Dynamic planar warping for optical character recognition , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[29] L. R. Dice. Measures of the Amount of Ecologic Association Between Species , 1945 .
[30] Geoffrey J. McLachlan,et al. Mixture models : inference and applications to clustering , 1989 .
[31] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[32] Andrew J. Viterbi,et al. Trellis Encoding of memoryless discrete-time sources with a fidelity criterion , 1974, IEEE Trans. Inf. Theory.
[33] James Llinas,et al. Comparative analysis of alternative ground target tracking techniques , 2000, Proceedings of the Third International Conference on Information Fusion.
[34] David A. Forsyth,et al. Learning the semantics of words and pictures , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[35] A. Constantinides,et al. A graph-theoretic approach to colour image segmentation and contour classification , 1992 .
[36] Alan C. Evans,et al. BrainWeb: Online Interface to a 3D MRI Simulated Brain Database , 1997 .
[37] James Ze Wang,et al. Stochastic modeling of volume images with a 3-D hidden Markov model , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..
[38] Robert M. Gray,et al. Image classification by a two-dimensional hidden Markov model , 2000, IEEE Trans. Signal Process..
[39] Bernard Mérialdo,et al. Semantic Image Segmentation with a Multidimensional Hidden Markov Model , 2007, MMM.
[40] Anjan Sarkar,et al. A simple unsupervised MRF model based image segmentation approach , 2000, IEEE Trans. Image Process..
[41] T Petrie,et al. Probabilistic functions of finite-state markov chains. , 1967, Proceedings of the National Academy of Sciences of the United States of America.
[42] Ron Kikinis,et al. Automatic Optimization of Segmentation Algorithms Through Simultaneous Truth and Performance Level Estimation (STAPLE) , 2004, MICCAI.
[43] Gerhard Rigoll,et al. Improved Face Recognition Using Pseudo 2-D Hidden Markov Models , 1998 .
[44] Eric Moulines,et al. Inference in hidden Markov models , 2010, Springer series in statistics.
[45] David A. Clausi,et al. Gaussian MRF rotation-invariant features for image classification , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] Ioannis Patras,et al. Video Segmentation by MAP Labeling of Watershed Segments , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[47] P. Devijver. PROBABILISTIC LABELING IN A HIDDEN SECOND ORDER MARKOV MESH , 1986 .
[48] H. Akaike. A new look at the statistical model identification , 1974 .
[49] Oscar E. Agazzi,et al. Machine vision for keyword spotting using pseudo 2D hidden Markov models , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[50] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[51] Roger C. Tam,et al. Image segmentation using an efficient rotationally invariant 3D region-based hidden Markov model , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.