Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging

Keyphrases

• Automatic Segmentation 100%
• Susceptibility-weighted Imaging 100%
• Convolutional Neural Network 100%
• Deep Brain nuclei 100%
• Multi-atlas Segmentation 66%
• Convolutional Neural Network Architecture 66%
• Brain Regions 33%
• Training Data 33%
• Inter-rater Reliability 33%
• Substantia Nigra 33%
• Human Brain 33%
• Strong Correlation 33%
• Segmentation Model 33%
• Subthalamic nucleus 33%
• Iron Deposition 33%
• MRI Techniques 33%
• Manual Annotation 33%
• In Vivo Quantification 33%
• Dentate nucleus 33%
• Red nucleus 33%
• External Data 33%
• Dice Coefficient 33%
• Iron-rich 33%
• Segmentation Approach 33%
• In Vivo Visualization 33%
• Prediction Strategy 33%
• Combined Prediction 33%
• Region Prediction 33%
• Regional Susceptibility 33%

Neuroscience

• Neural Network 100%
• Susceptibility Weighted Imaging 100%
• In Vivo 20%
• Substantia nigra 20%
• Magnetic Resonance Imaging 20%
• Subthalamic Nucleus 20%
• Dentate Nucleus 20%
• Red Nucleus 20%

Computer Science

• Convolutional Neural Network 100%
• Neural Network Architecture 33%
• Annotation 16%
• Training Dataset 16%
• Individual Variability 16%
• Segmentation Model 16%
• Segmentation Approach 16%