Table 1:

DMNet cell segmentation performance (OP_CSB) on CTC-6 of March 2021. All reported results are from the CTC Challenge website. The first row is OP_CSB and the second row is ranking compared to other submitted algorithms. Not all methods reported results for all datasets which are shown as NA. Since CALT-US did not report results for Fluo-C2DL-MSC we provide two sets of Rankings – 8 datasets and 7 datasets for equivalent comparison. Rank Sum is the sum of all the ranks across cell types. DMNet consistently outperforms other methods on 2D cell segmentation.

Dataset	BF-C2DL-HSC	BF-C2DL-MuSC	DIC-C2DH-HeLa	Fluo-C2DL-MSC	Fluo-N2DH-GOWT1	Fluo-N2DL-HeLa	PhC-C2DH-U373	PhC-C2DL-PSC	Avg	Rank Sum(8,7)
KIT-Sch-GE [35]	0.905	0.878	0.850	0.686	0.895	0.938	0.927	0.859	0.893
	1/14	1/14	14/27	6/32	20/42	11/40	15/30	1/33		69,63
PURD-US [58]	0.745	0.678	0.703	0.478	0.915	0.943	0.940	0.790	0.816
	13/14	14/14	19/27	24/32	14/42	6/40	11/30	13/33		114,90
CALT-US [9]	0.901	0.852	0.925	-	0.948	0.915	0.959	0.703	0.886
	2/14	4/14	1/27	-	3/42	18/40	1/30	25/33		NA,54
DMNet (Ours)	0.835	0.860	0.864	0.602	0.939	0.954	0.949	0.826	0.890
	10/14	3/14	12/27	17/32	5/42	1/40	6/30	6/33		60,43