A Novel Quality Control Algorithm for Medical Image Segmentation Based on Fuzzy Uncertainty

Keyphrases

• Area under the Receiver Operating Characteristic Curve 33%
• Breast 33%
• Clinical Setting 33%
• Deep Learning Applications 33%
• Deep Learning Methods 33%
• Deep Learning Segmentation 33%
• Dice Coefficient 33%
• Distance Transform Algorithm 33%
• Euclidean Distance Transform 33%
• Excellent Performance 33%
• Fuzziness 33%
• Fuzzy Sets 66%
• Fuzzy Uncertainty 100%
• Good Quality 33%
• Group Areas 33%
• Image Level 66%
• Image Segmentation 33%
• Inference Process 33%
• Lung 33%
• Medical Image Segmentation 100%
• Model Inference 33%
• Model Uncertainty 33%
• Monte Carlo Dropout 33%
• Pearson Correlation Coefficient 33%
• Poor Quality 33%
• Quality Control Algorithm 100%
• Quality Control Method 33%
• Quality Groups 33%
• Segmentation Model 66%
• Segmentation Quality 100%
• Segmentation Uncertainty 33%
• Segmentation-based 100%
• Skin Cells 33%
• Skin Lesions 33%
• Strong Correlation 33%
• Test Time Augmentation 33%
• Uncertain Data 33%

Engineering

• Control Algorithm 100%
• Deep Learning 66%
• Euclidean Distance Transform 33%
• Experimental Result 33%
• Fuzziness 33%
• Inference Process 33%
• Level Image 66%
• Medical Image Segmentation 100%
• Model Uncertainty 33%
• Operating Curve 33%
• Pearsons Linear Correlation Coefficient 33%
• Poor Quality 33%
• Quality Control 100%
• Segmentation Quality 100%
• Test Time 33%