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SOTA
医学图像分割
Medical Image Segmentation On Etis
Medical Image Segmentation On Etis
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
Columns
模型名称
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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