Deep learning for liver tumour classification: Enhanced loss function

Keyphrases

• Classification Accuracy 100%
• Processing Time 100%
• Loss Function 100%
• Deep Learning 100%
• Liver Tumor 100%
• Tumor Classification 100%
• Feature Extraction 50%
• Tumor 50%
• Support Vector Machine Classifier 50%
• Feature Classification 50%
• Regularization Method 50%
• MRI Images 50%
• Linear Map 50%
• Tumor Subtype 25%
• Feature Vector 25%
• Support Vector Machine 25%
• Early Diagnosis 25%
• Region of Interest 25%
• Selected Features 25%
• Current Loss 25%
• Affected Area 25%
• Hybrid Model 25%
• Image Noise 25%
• Image Enhancement 25%
• Probability Score 25%
• Noise Removal 25%
• Gray-level Co-occurrence 25%
• Computer-aided Diagnosis (CADx) 25%
• Total Execution Time 25%
• Weiner Filter 25%
• Liver MRI 25%
• Tumor Features 25%
• Filtering Algorithm 25%
• Region Growing Algorithm 25%
• Image Class 25%

Engineering

• Classification Accuracy 100%
• Processing Time 100%
• Loss Function 100%
• Deep Learning Method 100%
• Support Vector Machine 75%
• Feature Extraction 50%
• Linear Mapping 50%
• Regularization 50%
• Feature Vector 25%
• Hybrid Model 25%
• Filtering Algorithm 25%
• Extracted Feature 25%
• Region of Interest 25%
• Cooccurrence Matrix 25%
• Grey Level 25%
• Image Enhancement 25%
• Computer Aided Diagnosis 25%
• Execution Time 25%

Earth and Planetary Sciences

• Support Vector Machine 100%
• Pattern Recognition 66%
• Image Enhancement 33%