High-Resolution Encoder-Decoder Networks for Low-Contrast Medical Image Segmentation

Keyphrases

• High-resolution 100%
• Low Contrast 100%
• Encoder-decoder 100%
• Medical Image Segmentation 100%
• Skip Connection 100%
• High-resolution Encoder 100%
• Semantic Information 66%
• Magnetic Resonance Imaging 33%
• Brain Tumor 33%
• Radiation Therapy 33%
• Computer-aided 33%
• Modal 33%
• Disease Diagnosis 33%
• Recent Advances 33%
• Blurry Image 33%
• Disease Treatment 33%
• Model Performance 33%
• CT Images 33%
• Medical Image Analysis 33%
• Medical Image 33%
• Boundary Detection 33%
• Microscopic Image 33%
• 2D to 3D 33%
• Image Segmentation 33%
• Complex Boundary 33%
• Regression Task 33%
• Overall Modeling 33%
• CT Image Dataset 33%
• Segmentation Dataset 33%
• Convolutional Neural Network 33%
• Image Analysis Applications 33%
• Deep Learning Architectures 33%
• Pelvic CT 33%
• Semantic Feature Map 33%
• Automatic Image Segmentation 33%
• Boundary Localization 33%
• Dilated Convolution 33%
• Densely Connected 33%
• Cross-entropy Loss Function 33%
• Encoder-decoder Structure 33%
• Instance Segmentation 33%
• Treatment Effect Evaluation 33%
• Network Complexity 33%
• Multi-scale Dense Network 33%
• Deeply-supervised 33%
• 3D Semantic Segmentation 33%
• Contour Regression 33%
• Cell Segmentation 33%

Computer Science

• Image Segmentation 100%
• Experimental Result 20%
• Semantic Feature 20%
• Image Analysis 20%
• Performance Model 20%
• Treatment Effect 20%
• Microscopic Image 20%
• Boundary Detection 20%
• Regression Task 20%
• Convolutional Neural Network 20%
• Deep Architecture 20%
• Cross Entropy Loss Functions 20%
• Semantic Resolution 20%
• Instance Segmentation 20%
• Cell Segmentation 20%
• Feature Map 20%