Fig. 6
From: Efficient medical image segmentation using RepSegNet lightweight reparameterized neural network
RepSegNet performance on CVC-ClinicDB dataset. Visual results demonstrating model performance on colonoscopy images: (a, d) Original colonoscopy images showing polyps; (b, e) Ground truth segmentation masks; (c, f) Prediction masks generated by RepSegNet. The model achieves high accuracy in polyp boundary delineation even in areas with complex tissue patterns and varied illumination conditions.
