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홈
SOTA
의료 이미지 분할
Medical Image Segmentation On Cvc Colondb
Medical Image Segmentation On Cvc Colondb
평가 지표
mIoU
mean Dice
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
mIoU
mean Dice
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
0 of 23 row(s) selected.
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