Automated identification and quantification of metastatic brain tumors and perilesional edema based on a deep learning neural network

Keyphrases

• 3D Convolutional Neural Network (3D CNN) 25%
• 5-fold Cross Validation 25%
• Automated Identification 100%
• Automated Quantification 100%
• Automatic Segmentation 50%
• Brain Edema 25%
• Brain Parenchyma 50%
• Clinical Analysis 25%
• Contrast Enhancement 25%
• Deep Learning Model 50%
• Deep Learning Neural Network 100%
• Dice Similarity Coefficient 50%
• Edema 50%
• Extraction Model 25%
• Gamma Knife 25%
• Graphical User Interface 25%
• Initial Treatment 25%
• Intracranial Lesions 25%
• Mask Region-based Convolutional Neural Network 25%
• Metastatic Brain Tumor 100%
• Metastatic Tumor 50%
• Neurosurgeon 25%
• Perilesional Edema 100%
• Segmentation Model 25%
• Surgical Data 25%
• T1-weighted 25%
• T2-weighted Imaging (T2WI) 50%
• Treatment Plan 25%
• Tumor 50%

Neuroscience

• Intracranial Tumor 100%
• Magnetic Resonance Imaging 33%
• Neural Network 100%
• Parenchyma 66%