Medical Image Segmentation On Etis

mIoU

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	mIoU	mean Dice
meganet-multi-scale-edge-guided-attention	0.709	0.789
using-duck-net-for-polyp-image-segmentation-1	0.8788	0.9354
rsaformer-a-method-of-polyp-segmentation-with	-	0.835
duat-dual-aggregation-transformer-network-for	0.746	0.822
stepwise-feature-fusion-local-guides-global	0.720	0.796
esfpnet-efficient-deep-learning-architecture	0.748	0.823
emcad-efficient-multi-scale-convolutional	-	0.9229
meta-polyp-a-baseline-for-efficient-polyp	0.704	0.78
promise-promptable-medical-image-segmentation	0.750	0.840
uacanet-uncertainty-augmented-context	0.689	0.766
medical-image-segmentation-via-cascaded	0.7258	0.8007
resunet-an-advanced-architecture-for-medical	0.7534	0.6364
pranet-parallel-reverse-attention-network-for	0.5670	0.6280
meganet-multi-scale-edge-guided-attention	0.665	0.739
hardnet-mseg-a-simple-encoder-decoder-polyp	0.613	0.677
comma-propagating-complementary-multi-level	0.648	0.711
metaformer-and-cnn-hybrid-model-for-polyp	0.9179	0.9572
transfuse-fusing-transformers-and-cnns-for	0.661	0.737
transfuse-fusing-transformers-and-cnns-for	0.659	0.733
hardnet-dfus-an-enhanced-harmonically	-	0.730
caranet-context-axial-reverse-attention	0.672	0.747
uacanet-uncertainty-augmented-context	0.615	0.694
sam-eg-segment-anything-model-with-egde	0.681	0.757
a-comprehensive-study-on-colorectal-polyp	0.7458	0.6136