Segmenting Hepatic Lesions Using Residual Attention U-Net with an Adaptive Weighted Dice Loss

Keyphrases

• Adaptive Weight 100%
• Attention Module 25%
• Benchmark Dataset 25%
• Convolutional Layer 25%
• Dice Loss 100%
• Hepatic Lesion 100%
• Lesion Segmentation 25%
• Liver Tumor Segmentation 50%
• MICCAI 25%
• Network Architecture 25%
• Residual Attention 100%
• Residual Block 25%
• Skip Connection 25%
• Tumor 25%
• U-Net 100%

Computer Science

• Background Class 50%
• Convolutional Layer 50%
• Experimental Result 50%
• Lesion Segmentation 50%
• Network Architecture 50%
• Tumor Segmentation 100%
• U-Net 100%