Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks

Keyphrases

• Hepatocellular Carcinoma 100%
• Tumor 100%
• Automatic Segmentation 100%
• Convolutional Neural Network 100%
• Small Combination of Slices 83%
• Diffusion-weighted Imaging 66%
• Convolutional Neural Network Model 50%
• T1WI 50%
• Dice Similarity Coefficient 50%
• Volumetric Segmentation 33%
• Semi-automated 33%
• T2-weighted Imaging (T2WI) 33%
• Tumor Size 33%
• MRI Sequences 33%
• Volume-of-interest 33%
• Post-contrast 33%
• Interobserver Agreement 16%
• Neural Network 16%
• Statistical Significance 16%
• Before Surgery 16%
• Manual Segmentation 16%
• Radiologists 16%
• T1-weighted Imaging 16%
• Single-center Study 16%
• Interobserver Reproducibility 16%
• B-value 16%
• Segmentation Performance 16%
• Volumetric Approach 16%
• Validation Set 16%
• Lesion Size 16%
• Model Performance 16%
• Contrast Phase 16%
• Segmentation Analysis 16%
• Index Lesion 16%
• Portal Venous 16%
• Large Lesions 16%
• Hepatobiliary Phase 16%
• Segmentation Accuracy 16%
• Coefficient Test 16%
• Gadoxetate 16%

Medicine and Dentistry

• Hepatocellular Carcinoma 100%
• Neoplasm 100%
• Magnetic Resonance Imaging 100%
• Diffusion MRI 66%
• Povidone 33%
• Reproducibility 16%
• Gadoxetic Acid 16%

Biochemistry, Genetics and Molecular Biology

• Magnetic Resonance Imaging 100%
• Facilitated Diffusion 66%
• Tumor Volume 33%
• Gadoxetic Acid 16%