Continuous Voxel Classification by Stochastic Relaxation: Theory and Application to MR Imaging and MR Angiography

In this paper we present a stochastic relaxation method based on Bayesian decision theory for voxel classification in medical images. The labels are continuous (as opposed to discrete) values representing the degree of belief that a voxel belongs to a certain object class.

[1]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[2]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .

[3]  J. Laurie Snell,et al.  Markov Random Fields and Their Applications , 1980 .

[4]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  J. Besag.  On the Statistical Analysis of Dirty Pictures , 1986 .

[6]  Haluk Derin,et al.  Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Tomaso Poggio,et al.  Probabilistic Solution of Ill-Posed Problems in Computational Vision , 1987 .

[8]  W. Wong,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[9]  Pat Hanrahan,et al.  Volume Rendering , 2020, Definitions.

[10]  Marc Levoy,et al.  Display of surfaces from volume data , 1988, IEEE Computer Graphics and Applications.

[11]  Terry M. Peters,et al.  A Volume of Interest (VOI) Atlas for the Analysis of Neurophysiological Image Data , 1989, Medical Imaging.

[12]  Sridhar Lakshmanan,et al.  Simultaneous Parameter Estimation and Segmentation of Gibbs Random Fields Using Simulated Annealing , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Bernard Chalmond,et al.  An iterative Gibbsian technique for reconstruction of m-ary images , 1989, Pattern Recognit..

[14]  James M. Coggins,et al.  Biomedical image segmentation using multiscale orientation fields , 1990, [1990] Proceedings of the First Conference on Visualization in Biomedical Computing.

[15]  D. Louis Collins,et al.  Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis , 1991, Medical Imaging.

[16]  Stephen M. Pizer,et al.  Boundary Estimation in Ultrasound Images , 1991, IPMI.

[17]  Wesley E. Snyder,et al.  Segmentation of magnetic resonance images using mean field annealing , 1992, Image Vis. Comput..

[18]  Guido Gerig,et al.  Unsupervised tissue type segmentation of 3D dual-echo MR head data , 1992, Image Vis. Comput..

[19]  Guido Gerig,et al.  Nonlinear anisotropic filtering of MRI data , 1992, IEEE Trans. Medical Imaging.

[20]  G. Marchal,et al.  Magnetic resonance voxel labeling based on Bayesian Decision Theory , 1993 .