Semi-supervised and active learning for automatic segmentation of Crohn's disease

Keyphrases

• Active Learning 100%
• Semi-supervised Learning 100%
• Automatic Segmentation 100%
• Crohn's Disease 100%
• Learnability 25%
• Contextual Information 25%
• Random Forest Classifier 25%
• Semantic Knowledge 25%
• Semantic Labeling 25%
• Few Samples 25%
• Magnetic Resonance Imaging 25%
• Information Semantics 25%
• Automatic Detection 25%
• Supervised Methods 25%
• Segmentation Accuracy 25%
• Learning Classification 25%
• High Classification Accuracy 25%
• Abdominal 25%
• Information Density 25%
• Weighting Approach 25%
• Knowledge Uncertainty 25%
• Density Weight 25%
• Label Ambiguity 25%
• Fully-supervised 25%

Computer Science

• Supervised Learning 100%
• Active Learning 100%
• Automatic Segmentation 100%
• Semisupervised Learning 75%
• Supervised Method 25%
• Random Forest Classifier 25%
• segmentation accuracy 25%
• Context Information 25%
• Experimental Result 25%
• Classification Accuracy 25%
• Semantic Knowledge 25%
• Automatic Detection 25%