Medical Image Segmentation On Etis

المقاييس

mIoU

mean Dice

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

			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

المقاييس

النتائج