Medical Image Segmentation On Kvasir Seg
評価指標
Average MAE
mean Dice
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
比較表
| モデル名 | Average MAE | mean Dice |
|---|---|---|
| fanet-a-feedback-attention-network-for | 0.8153 | 0.8803 |
| a-comprehensive-study-on-colorectal-polyp | - | 0.8508 |
| rupnet-residual-upsampling-network-for-real | - | 0.7658 |
| tganet-text-guided-attention-for-improved | - | 0.8982 |
| esfpnet-efficient-deep-learning-architecture | - | 0.931 |
| transnetr-transformer-based-residual-network | - | 0.8706 |
| real-time-polyp-detection-localisation-and | - | 0.8206 |
| comma-propagating-complementary-multi-level | 0.024 | 0.904 |
| effisegnet-gastrointestinal-polyp | - | 0.9483 |
| hardnet-dfus-an-enhanced-harmonically | - | 0.9363 |
| dual-cross-attention-for-medical-image | - | 0.8516 |
| meganet-multi-scale-edge-guided-attention | 0.026 | 0.911 |
| hardnet-mseg-a-simple-encoder-decoder-polyp | 0.025 | 0.912 |
| uacanet-uncertainty-augmented-context | 0.026 | 0.905 |
| ag-curesnest-a-novel-method-for-colon-polyp | - | 0.902 |
| spatially-exclusive-pasting-a-general-data | - | 0.9411 |
| comma-propagating-complementary-multi-level | 0.027 | 0.901 |
| metaformer-and-cnn-hybrid-model-for-polyp | - | 0.939 |
| msrf-net-a-multi-scale-residual-fusion | - | 0.9217 |
| emcad-efficient-multi-scale-convolutional | - | 0.928 |
| stepwise-feature-fusion-local-guides-global | - | 0.9357 |
| self-prompting-polyp-segmentation-in | - | 0.866 |
| transfuse-fusing-transformers-and-cnns-for | - | 0.918 |
| transresu-net-transformer-based-resu-net-for | - | 0.8884 |
| effisegnet-gastrointestinal-polyp | - | 0.9488 |
| duat-dual-aggregation-transformer-network-for | 0.023 | 0.924 |
| kvasir-seg-a-segmented-polyp-dataset | - | 0.7877 |
| using-duck-net-for-polyp-image-segmentation-1 | - | 0.9502 |
| medical-image-segmentation-via-cascaded | - | 0.9258 |
| caranet-context-axial-reverse-attention | 0.023 | 0.918 |
| transfuse-fusing-transformers-and-cnns-for | - | 0.918 |
| s2s2-semantic-stacking-for-robust-semantic | - | 0.932 |
| uacanet-uncertainty-augmented-context | 0.025 | 0.912 |
| promise-promptable-medical-image-segmentation | - | 0.911 |
| unet-a-nested-u-net-architecture-for-medical | 0.048 | 0.8210 |
| bdg-net-boundary-distribution-guided-network | 0.021 | 0.915 |
| fcn-transformer-feature-fusion-for-polyp | - | 0.9385 |
| rabit-an-efficient-transformer-using | - | 0.927 |
| adaptive-t-vmf-dice-loss-for-multi-class | - | 0.9445 |
| gmsrf-net-an-improved-generalizability-with | - | 0.9263 |
| g-cascade-efficient-cascaded-graph | - | 0.9274 |
| kdas3-knowledge-distillation-via-attention | 0.027 | 0.913 |
| polyp-sam-can-a-text-guided-sam-perform | - | 0.902 |
| adaptation-of-distinct-semantics-for | - | 0.92 |
| ugcanet-a-unified-global-context-aware | - | 0.928 |
| fcb-swinv2-transformer-for-polyp-segmentation | - | 0.9420 |
| ddanet-dual-decoder-attention-network-for | - | 0.8576 |
| lm-net-a-light-weight-and-multi-scale-network | - | 0.9409 |
| u-net-convolutional-networks-for-biomedical | 0.055 | 0.8180 |
| meganet-multi-scale-edge-guided-attention | 0.025 | 0.913 |
| sam-eg-segment-anything-model-with-egde | - | 0.915 |
| resunet-an-advanced-architecture-for-medical | - | 0.8133 |
| multi-kernel-positional-embedding-convnext | - | 0.8818 |
| colonformer-an-efficient-transformer-based | - | 0.927 |
| a-denseunet-adaptive-densely-connected-unet | - | 0.9085 |
| pranet-parallel-reverse-attention-network-for | 0.030 | 0.898 |