Myocardium segmentation combining T2 and DE MRI using Multi-Component Bivariate Gaussian mixture model.
Jie LiuXiahai ZhuangJing LiuShaoting ZhangGuotai WangLianming WuJianrong XuLixu GuPublished in: ISBI (2014)
Keyphrases
- gaussian mixture model
- multi component
- brain scans
- medical images
- background subtraction
- mixture model
- accurate segmentation
- long axis
- magnetic resonance imaging
- feature vectors
- intensity distribution
- mr images
- mri images
- bayesian information criterion
- segmentation algorithm
- automatic segmentation
- gaussian distribution
- em algorithm
- left ventricle
- magnetic resonance images
- mri data
- expectation maximization
- maximum likelihood
- medical imaging
- brain tumors
- fully automatic
- segmentation method
- displacement field
- manual segmentation
- image segmentation
- feature space
- gaussian model
- tagged mri
- multiscale
- carotid artery
- non stationary
- myocardial perfusion
- feature extraction
- maximum likelihood criterion
- motion estimation
- high resolution
- short axis
- mouth region
- unsupervised learning
- left ventricular
- object segmentation
- image intensity
- machine learning