Medical Image Segmentation On Etis

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mIoU

mean Dice

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

			Paper Title	Repository
RAPUNet	0.9179	0.9572	MetaFormer and CNN Hybrid Model for Polyp Image Segmentation	-
DUCK-Net	0.8788	0.9354	Using DUCK-Net for Polyp Image Segmentation
EMCAD	-	0.9229	EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
ProMISe	0.750	0.840	ProMISe: Promptable Medical Image Segmentation using SAM
RSAFormer	-	0.835	RSAFormer: A method of polyp segmentation with region self-attention transformer	-
ESFPNet-L	0.748	0.823	ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video
DuAT	0.746	0.822	DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation
PVT-CASCADE	0.7258	0.8007	Medical Image Segmentation via Cascaded Attention Decoding	-
SSFormer-L	0.720	0.796	Stepwise Feature Fusion: Local Guides Global
MEGANet(ResNet-34)	0.709	0.789	MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation
Meta-Polyp	0.704	0.78	Meta-Polyp: a baseline for efficient Polyp segmentation
UACANet-L	0.689	0.766	UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation
SAM-EG	0.681	0.757	SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation	-
CaraNet	0.672	0.747	CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
MEGANet(Res2Net-50)	0.665	0.739	MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation
TransFuse-L	0.661	0.737	TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
TransFuse-S	0.659	0.733	TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
HarDNet-DFUS	-	0.730	HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp Segmentation
COMMA (Res2Net-50)	0.648	0.711	COMMA: Propagating Complementary Multi-Level Aggregation Network for Polyp Segmentation	-
UACANet-S	0.615	0.694	UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation

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Medical Image Segmentation On Etis

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