Bayesian Network and Structured Random Forest Cooperative Deep Learning For Automatic Multi-label Brain Tumor Segmentation

Keyphrases

• Auto-context 9%
• Bayesian Network 100%
• Bayesian Network Classifiers 9%
• Boundary Segmentation 9%
• Brain Cancer 9%
• Brain Tumor Segmentation 100%
• Cancer Phenotyping 9%
• Cancer Treatment 9%
• Classification Task 9%
• Comparison Method 9%
• Cooperative Learning 36%
• Deep Learning 100%
• Deep Learning Architectures 9%
• Extracting Features 9%
• Fluid-attenuated Inversion Recovery (FLAIR) 9%
• Fully Automated 9%
• Image Components 9%
• Image Information 9%
• Image Intensity 9%
• Image Shape 9%
• Image Texture 9%
• Layered Structure 9%
• Learning Framework 9%
• Medical Image Analysis 9%
• Multi-label Classification 9%
• Multilevel Framework 9%
• Multimodal Images 9%
• Multimodal MR Images 18%
• Network Segmentation 9%
• Nonoperative 9%
• Pixel Level 9%
• Probability Map 9%
• Radiomics 9%
• Radiomics Analysis 9%
• Segmentation Map 18%
• Segmentation Method 9%
• Statistical Dependence 9%
• Structured Random Forest 100%
• Superpixel 9%
• Transfer Learning 9%
• Tumor 9%
• Tumor Boundary 9%
• Tumor Features 9%
• Tumor Image 9%
• Whole Tumor 9%

Computer Science

• Bayesian Networks 100%
• Classification Task 8%
• Deep Architecture 8%
• Deep Learning Method 100%
• Image Information 8%
• Image Intensity 8%
• Learning Framework 8%
• Multi-Label Classification 8%
• Network Segmentation 8%
• Original Multi 8%
• Probability Map 8%
• Random Decision Forest 100%
• Segmentation Map 16%
• Segmentation Method 8%
• Superpixel 8%
• Transfer Learning 8%
• Tumor Segmentation 100%