Automated brain tumor segmentation from multimodal MRI data based on Tamura texture feature and an ensemble SVM classifier.
Li NaXiong ZhiyongDeng TianqiRen KaiPublished in: Int. J. Intell. Comput. Cybern. (2019)
Keyphrases
- mri data
- svm classifier
- texture features
- feature vectors
- brain tumor segmentation
- magnetic resonance images
- fully automatic
- support vector machine
- training set
- magnetic resonance imaging
- mr images
- support vector machine svm
- image classification
- support vector
- image features
- synthetic data
- color features
- texture analysis
- white matter
- feature extraction
- gabor filters
- texture feature extraction
- distance measure
- texture images
- shape features
- kernel function
- local binary pattern
- feature set
- medical images
- brain tumors
- feature space
- training data
- gray level
- semi automatic
- medical imaging
- semi supervised
- neural network
- data sets
- texture descriptors
- magnetic resonance
- image data
- high quality
- k nearest neighbor
- similarity measure
- face recognition
- image segmentation
- feature selection
- diffusion tensor
- textural features
- learning algorithm
- gaussian mixture model