One-Pass Multi-Task Networks With Cross-Task Guided Attention for Brain Tumor Segmentation

Keyphrases

• Multi-task Network 100%
• Guided Attention 100%
• Brain Tumor Segmentation 100%
• Cross-task 100%
• Model Cascade 75%
• Deep Model 50%
• Class Imbalance 50%
• Result Prediction 50%
• BraTS 50%
• Training Data 25%
• Publicly Available 25%
• Segmentation Problem 25%
• Popular 25%
• Excellent Performance 25%
• Learning-based 25%
• Discriminative Features 25%
• Training Strategy 25%
• Medical Image Segmentation 25%
• Validation Set 25%
• Post-processing Techniques 25%
• Data Transfer 25%
• Specific Parameters 25%
• Art Performance 25%
• Attention Network 25%
• Online Training 25%
• Third Place 25%
• Attention Module 25%
• Cascaded Approach 25%
• Joint Feature 25%
• Shared Parameters 25%
• Coarse-to-fine Segmentation 25%
• Transfer Strategy 25%
• Response-adapted 25%
• BraTS 2018 25%
• Cascade Strategy 25%
• Category-specific 25%
• Channel-wise Feature 25%
• Joint Task 25%
• Online Validation 25%
• System Complexity 25%
• Class Imbalance Issue 25%
• Curriculum Learning 25%
• Lightweight Deep Model 25%

Computer Science

• Class Imbalance 100%
• Tumor Segmentation 100%
• Training Data 33%
• Image Segmentation 33%
• Segmentation Task 33%
• Discriminative Feature 33%
• Outstanding Performance 33%
• Attention (Machine Learning) 33%
• Postprocessing Method 33%
• Art Performance 33%
• Validation Set 33%
• System Complexity 33%
• Data Transfer Strategy 33%