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Medical Image Segmentation On Kvasir Seg

Metrics

Average MAE
mean Dice

Results

Performance results of various models on this benchmark

Paper Title
DUCK-Net-0.9502Using DUCK-Net for Polyp Image Segmentation
EffiSegNet-B5-0.9488EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder
EffiSegNet-B4-0.9483EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder
FCB Former-0.9445Adaptive t-vMF Dice Loss for Multi-class Medical Image Segmentation
FCB-SwinV2 Transformer-0.9420FCB-SwinV2 Transformer for Polyp Segmentation
SEP-0.9411Spatially Exclusive Pasting: A General Data Augmentation for the Polyp Segmentation
LM-Net-0.9409LM-Net: A Light-weight and Multi-scale Network for Medical Image Segmentation
RAPUNet-0.939MetaFormer and CNN Hybrid Model for Polyp Image Segmentation
FCBFormer-0.9385FCN-Transformer Feature Fusion for Polyp Segmentation
HarDNet-DFUS-0.9363HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp Segmentation
SSFormer-L-0.9357Stepwise Feature Fusion: Local Guides Global
FCBFormer-0.932S2S2: Semantic Stacking for Robust Semantic Segmentation in Medical Imaging
ESFPNet-L-0.931ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video
EMCAD-0.928EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
UGCANet-0.928UGCANet: A Unified Global Context-Aware Transformer-based Network with Feature Alignment for Endoscopic Image Analysis
PVT-GCASCADE-0.9274G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation
RaBiT-0.927RaBiT: An Efficient Transformer using Bidirectional Feature Pyramid Network with Reverse Attention for Colon Polyp Segmentation
ColonFormer-0.927ColonFormer: An Efficient Transformer based Method for Colon Polyp Segmentation
GMSRF-Net-0.9263GMSRF-Net: An improved generalizability with global multi-scale residual fusion network for polyp segmentation
PVT-CASCADE-0.9258Medical Image Segmentation via Cascaded Attention Decoding
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