Medical Image Segmentation On Cvc Colondb

评估指标

mIoU

mean Dice

评测结果

各个模型在此基准测试上的表现结果

			Paper Title	Repository
RAPUNet	0.9096	0.9526	MetaFormer and CNN Hybrid Model for Polyp Image Segmentation	-
DUCK-Net	0.8785	0.9353	Using DUCK-Net for Polyp Image Segmentation
EMCAD	-	0.9231	EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
ProMISe	0.789	0.874	ProMISe: Promptable Medical Image Segmentation using SAM
Meta-Polyp	0.79	0.867	Meta-Polyp: a baseline for efficient Polyp segmentation
ResUNet++ + TTA	0.8466	0.8474	A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation
PVT-GCASCADE	0.7460	0.8261	G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation
PVT-CASCADE	0.7453	0.8254	Medical Image Segmentation via Cascaded Attention Decoding	-
DuAT	0.737	0.819	DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation
ESFPNet-L	0.730	0.811	ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video
Polyp-PVT	0.727	0.808	Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
SSFormer-L	0.721	0.802	Stepwise Feature Fusion: Local Guides Global
UACANet-S	0.704	0.783	UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation
SAM-EG	0.689	0.774	SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation	-
HarDNet-DFUS	-	0.774	HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp Segmentation
TransFuse-S	0.696	0.773	TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
CaraNet	0.689	0.773	CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
KDAS	0.679	0.759	KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation
COMMA (Res2Net-50)	0.689	0.754	COMMA: Propagating Complementary Multi-Level Aggregation Network for Polyp Segmentation	-
UACANet-L	0.678	0.751	UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation

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