Strided U-Net model: Retinal vessels segmentation using dice loss

Keyphrases

• Retinal Vessel Segmentation 100%
• Convolutional Neural Network 100%
• Dice Loss 100%
• U-Net 100%
• Retinal Image 66%
• Dice Loss Function 66%
• Preprocessing Techniques 33%
• Deep Learning Methods 33%
• Segmentation Method 33%
• Staring 33%
• DRIVE Database 33%
• Image Processing 33%
• Detection Accuracy 33%
• Training Process 33%
• Retinal Fundus Images 33%
• Medical Image Analysis 33%
• STARE Database 33%
• Accurate Segmentation 33%
• Uneven Illumination 33%
• Convolutional Neural Network Model 33%
• Variational Autoencoder 33%
• Pooling Layer 33%

Computer Science

• Vessel Segmentation 100%
• Convolutional Neural Network 100%
• U-Net 100%
• Image Processing 25%
• Neural Network Model 25%
• Preprocessing Step 25%
• Modified Version 25%
• Deep Learning 25%
• Training Process 25%
• Segmentation Method 25%

Engineering

• Convolutional Neural Network 100%
• Loss Function 50%
• Deep Layer 25%
• Segmentation Method 25%
• Medical Image 25%
• Input Image 25%
• Processing Step 25%
• Image Processing 25%
• Tasks 25%
• Network Model 25%
• Deep Learning 25%