Multi-tissue Nucleus Segmentation on Kumar

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Dice

Rank	Model	Dice	Hausdorff Distance (mm)	Jaccard Index	PQ	Paper	Code	Year
1	GC-MHVN	0.843	–	0.652	0.625	MRL: Learning to Mix with Attention and Convolutions		2022
2	DSF-CNN (C8)	0.826	60	–	–	Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images	simongraham/dsf-cnn · ladislasl/CNN_invar_rot	2020
2	HoVer-Net (e)	0.826	59.7	–	–	HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images	vqdang/xy_net · vqdang/hover_net · okunator/Dippa · +1	2018
4	Steerable G-CNN (C12)	0.820	55.8	–	–	Learning Steerable Filters for Rotation Equivariant CNNs		2017
5	CIA-Net (e)	0.818	57.7	–	–	CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation		2019
5	Steerable G-CNN (C12)	0.818	54.3	–	–	Learning Steerable Filters for Rotation Equivariant CNNs		2017
7	G-CNN (C12)	0.814	53.4	–	–	Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis	tueimage/se2cnn	2020
8	VF-CNN (C12)	0.813	51.4	–	–	Rotation equivariant vector field networks	COGMAR/RotEqNet · di-marcos/RotEqNet · ojas97/roteqnetp3	2016
9	G-CNN (C12)	0.811	51.9	–	–	Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis	tueimage/se2cnn	2020
10	Steerable G-CNN (C4)	0.809	54.2	–	–	Learning Steerable Filters for Rotation Equivariant CNNs		2017
11	VF-CNN (C12)	0.808	50.7	–	–	Rotation equivariant vector field networks	COGMAR/RotEqNet · di-marcos/RotEqNet · ojas97/roteqnetp3	2016
12	VF-CNN (C4)	0.800	49.9	–	–	Rotation equivariant vector field networks	COGMAR/RotEqNet · di-marcos/RotEqNet · ojas97/roteqnetp3	2016
13	Micro-Net (e)	0.797	51.9	–	–	Micro-Net: A unified model for segmentation of various objects in microscopy images		2018
13	FCN8 (e)	0.797	31.2	–	–	Fully Convolutional Networks for Semantic Segmentation	pochih/fcn-pytorch · andyzeng/apc-vision-toolbox · martinkersner/py_img_seg_eval · +48	2014
15	G-CNN (C4)	0.793	49.0	–	–	Group Equivariant Convolutional Networks	adambielski/pytorch-gconv-experiments	2016
16	Steerable G-CNN (e)	0.791	51.0	–	–	Learning Steerable Filters for Rotation Equivariant CNNs		2017
17	Mask R-CNN (e)	0.760	50.9	–	–	Mask R-CNN	tensorflow/models · facebookresearch/detectron2 · facebookresearch/detectron · +176	2017
18	U-Net (e)	0.758	47.8	–	–	U-Net: Convolutional Networks for Biomedical Image Segmentation	labmlai/annotated_deep_learning_paper_implementations · milesial/Pytorch-UNet · open-mmlab/mmsegmentation · +484	2015