| MetaFormer and CNN Hybrid Model for Polyp Image Segmentation | ✓ Link | 0.9526 | | | | 0.9096 | RAPUNet | 2024-09-16 |
| Using DUCK-Net for Polyp Image Segmentation | ✓ Link | 0.9353 | | | | 0.8785 | DUCK-Net | 2023-11-03 |
| EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation | ✓ Link | 0.9231 | | | | | EMCAD | 2024-05-11 |
| From Semantic Segmentation of Natural Images to Medical Image Segmentation Using ViT-Based Architectures | | 0.921 | | | | 0.854 | SegMed | 2025-01-31 |
| UniNet: A Contrastive Learning-guided Unified Framework with Feature Selection for Anomaly Detection | ✓ Link | 0.919 | | | | 0.856 | UniNet | 2025-02-28 |
| ProMISe: Promptable Medical Image Segmentation using SAM | ✓ Link | 0.874 | | | | 0.789 | ProMISe | 2024-03-07 |
| Meta-Polyp: a baseline for efficient Polyp segmentation | ✓ Link | 0.867 | | | | 0.79 | Meta-Polyp | 2023-05-13 |
| A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation | ✓ Link | 0.8474 | | | | 0.8466 | ResUNet++ + TTA | 2021-07-26 |
| G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation | ✓ Link | 0.8261 | | | | 0.7460 | PVT-GCASCADE | 2023-10-24 |
| Medical Image Segmentation via Cascaded Attention Decoding | ✓ Link | 0.8254 | | | | 0.7453 | PVT-CASCADE | 2023-01-03 |
| DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation | ✓ Link | 0.819 | 0.026 | | | 0.737 | DuAT | 2022-12-21 |
| ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video | ✓ Link | 0.811 | | | | 0.730 | ESFPNet-L | 2022-07-15 |
| Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers | ✓ Link | 0.808 | 0.031 | 0.865 | 0.913 | 0.727 | Polyp-PVT | 2021-08-16 |
| Stepwise Feature Fusion: Local Guides Global | ✓ Link | 0.802 | | | | 0.721 | SSFormer-L | 2022-03-07 |
| UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation | ✓ Link | 0.783 | 0.034 | 0.848 | 0.897 | 0.704 | UACANet-S | 2021-07-06 |
| SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation | | 0.774 | | | | 0.689 | SAM-EG | 2024-06-21 |
| HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp Segmentation | ✓ Link | 0.774 | | | | | HarDNet-DFUS | 2022-09-15 |
| CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects | ✓ Link | 0.773 | 0.042 | 0.853 | 0.902 | 0.689 | CaraNet | 2021-08-16 |
| TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation | ✓ Link | 0.773 | | | | 0.696 | TransFuse-S | 2021-02-16 |
| KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation | ✓ Link | 0.759 | 0.032 | | | 0.679 | KDAS | 2023-12-13 |
| COMMA: Propagating Complementary Multi-Level Aggregation Network for Polyp Segmentation | | 0.754 | 0.037 | 0.849 | 0.897 | 0.689 | COMMA (Res2Net-50) | 2022-02-17 |
| UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation | ✓ Link | 0.751 | 0.039 | 0.835 | 0.878 | 0.678 | UACANet-L | 2021-07-06 |
| TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation | ✓ Link | 0.744 | | | | 0.676 | TransFuse-L | 2021-02-16 |
| HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS | ✓ Link | 0.731 | | | | 0.660 | HarDNet-MSEG | 2021-01-18 |
| PraNet: Parallel Reverse Attention Network for Polyp Segmentation | ✓ Link | 0.709 | 0.045 | 0.819 | 0.869 | 0.649 | PraNet | 2020-06-13 |