Automatic prostate cancer detection model based on ensemble VGGNet feature generation and NCA feature selection using magnetic resonance images.
Mustafa KocSuat Kamil SutIhsan SerhatliogluMehmet BayginTürker TuncerPublished in: Multim. Tools Appl. (2022)
Keyphrases
- magnetic resonance images
- feature generation
- prostate cancer
- mr images
- feature selection
- text categorization
- medical image analysis
- medical images
- magnetic resonance
- inductive learning
- word sense disambiguation
- magnetic resonance imaging
- white matter
- feature representations
- mri data
- diffusion tensor
- statistical approaches
- accurate segmentation
- image data
- brain tumors
- medical imaging
- deformable registration
- machine learning
- text classification
- information extraction
- computer aided
- magnetic resonance spectroscopy
- training data
- generation method
- high resolution
- support vector
- random forests
- feature extraction
- neural network
- dimensionality reduction
- statistical modeling
- training set
- classifier ensemble
- feature space
- anatomical structures
- image processing
- random forest