Noise Resilience in Dermoscopic Image Segmentation: Comparing Deep Learning Architectures for Enhanced Accuracy

Keyphrases

• Accuracy Improvement 100%
• Deep Learning Architectures 100%
• MultiResUNet 100%
• Noise Resilience 100%
• Dermoscopic Image Segmentation 100%
• U-Net 80%
• Dermoscopic 60%
• Image Features 40%
• Low Quality Data 20%
• Sensitivity Specificity 20%
• Generative Adversarial Networks 20%
• Color Image 20%
• Deep Learning Framework 20%
• Segmentation Framework 20%
• Segmentation Performance 20%
• Dice Coefficient 20%
• New Architecture 20%
• Data Issues 20%
• Gaussian Noise 20%
• Medical Imaging 20%
• Melanoma 20%
• Skin Lesions 20%
• Sensitivity Coefficient 20%
• Accurate Localization 20%
• Segmentation Mask 20%
• Skin Diseases 20%
• Common Strategies 20%
• Lesion Annotation 20%
• Edge Deep Learning 20%
• Skin Lesion Analysis 20%
• Enhanced Imaging 20%
• Jaccard Coefficient 20%

Computer Science

• U-Net 100%
• Image Segmentation 100%
• Deep Learning Method 100%
• Annotation 25%
• Generative Adversarial Networks 25%
• Learning Framework 25%
• image feature 25%
• Medical Imaging 25%
• Segmentation Performance 25%
• Discriminator 25%
• Gaussian White Noise 25%
• Jaccard Coefficient 25%

Medicine and Dentistry

• Skin Defect 100%
• Diagnostic Imaging 50%
• Melanoma 50%
• Dermatosis 50%