CT Male Pelvic Organ Segmentation via Hybrid Loss Network with Incomplete Annotation

Keyphrases

• Segmentation Performance 100%
• Loss Networks 100%
• Organ Segmentation 100%
• Male Pelvic Organ 100%
• Hybrid Loss 100%
• Incomplete Annotation 100%
• Accurate Segmentation 33%
• Training Data 33%
• State-of-the-art Techniques 33%
• Shape Variation 33%
• Bone Structure 33%
• Low Contrast 33%
• Real Application 33%
• Manual Annotation 33%
• CT Images 33%
• Region-based 33%
• Automatic Segmentation 33%
• Human Effort 33%
• Planning CT 33%
• Computation Complexity 33%
• Data to Enhance 33%
• Specific Model 33%
• Annotated Dataset 33%
• Deep Model 33%
• Boundary Regression 33%
• Classification via Regression 33%
• Pelvic Organs 33%
• Manual Contouring 33%
• Medical Professionals 33%
• Pelvic Region 33%
• Completion Strategy 33%
• Model Capabilities 33%
• Label Completion 33%
• Voxel Classification 33%

Computer Science

• Annotation 100%
• Segmentation Performance 50%
• Experimental Result 16%
• Training Data 16%
• Shape Variation 16%
• Computation Complexity 16%
• Real Application 16%
• Sufficient Data 16%
• Segmentation Candidate 16%