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홈
SOTA
의료 이미지 분할
Medical Image Segmentation On Etis
Medical Image Segmentation On Etis
평가 지표
mIoU
mean Dice
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
mIoU
mean Dice
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
0 of 24 row(s) selected.
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