A novel cerebrovascular segmentation approach based on Markov random field and particle swarm optimization algorithm.
Rongfei CaoXingce WangZhongke WuMingquan ZhouYun TianXinyu LiuPublished in: VRCAI (2013)
Keyphrases
- markov random field
- particle swarm optimization algorithm
- mrf model
- image segmentation
- energy function
- particle swarm optimization
- iterated conditional modes
- textured images
- mrf models
- graph cuts
- prior model
- label field
- markov random field model
- energy minimization
- higher order
- segmentation algorithm
- pso algorithm
- belief propagation
- convergence speed
- conditional random fields
- parameter estimation
- maximum a posteriori
- pairwise
- image restoration
- random fields
- gibbs energy
- object segmentation
- discriminative random fields
- segmentation method
- medical images
- potential functions
- level set
- spatial continuity
- region growing
- multiscale
- image processing
- differential evolution
- map estimation
- computer vision
- labeling problems
- mrf optimization
- neural network
- genetic algorithm
- smoothness prior
- prior knowledge
- bayesian estimation
- image intensity