Fetal brain tissue annotation and segmentation challenge results

Keyphrases

• Annotation Datasets 50%
• Automated Segmentation Methods 50%
• Automatic Segmentation 50%
• Brain Development 100%
• Brain MRI Reconstruction 50%
• Brain Tissue 100%
• Brainstem 50%
• Cerebellum 50%
• Cerebral Structure 50%
• Cerebrospinal Fluid 50%
• Clinical Perspective 50%
• Clinical Setting 50%
• Deep Gray Matter 50%
• Deep Learning Framework 50%
• Deep Learning Methods 50%
• Ensemble Learning Method 50%
• Fetal Brain 100%
• Fetal Brain MRI 50%
• Fetal MRI 50%
• Fetal Tissue 100%
• Gray Matter 50%
• Image Processing 50%
• International Teams 50%
• Interobserver Variability 50%
• Manual Segmentation 50%
• Medical Imaging 50%
• Multi-tissue 50%
• Network Architecture 50%
• Network Images 50%
• Neural Architecture Optimization 50%
• Neurodevelopment 50%
• Open Dataset 50%
• Post-processing Techniques 50%
• Segmentation Algorithm 50%
• Segmentation Challenge 100%
• Step Performed 50%
• Technical Perspective 50%
• Tissue Segmentation 50%
• U-Net 100%
• Ventricle 50%
• White Matter 50%

Neuroscience

• Brainstem 50%
• Cerebellum 50%
• Gray Matter 100%
• Human Brain 100%
• Magnetic Resonance Imaging 50%
• Magnetic Resonance Imaging of Brain 50%
• Nerve Cell Differentiation 50%

Biochemistry, Genetics and Molecular Biology

• Magnetic Resonance Imaging 100%
• Nerve Cell Differentiation 50%
• Quantitative Technique 50%
• Reconstruction 50%