Table 3.

The performance comparison of different nuclei segmentation methods measured by region- and distance-based metrics on GBM40 dataset and TCGA dataset.

Methods	GBM40 dataset					TCGA dataset
	$J$	$P$	$R$	$F_1$	$H$	$J$	$P$	$R$	$F_1$	$H$
MS38	$0.44\pm 0.27$	$0.48\pm 0.30$	$0.90\pm 0.17$	$0.56\pm 0.27$	$29.20\pm 28.94$	$0.41\pm 0.26$	$0.52\pm 0.32$	$0.76\pm 0.26$	$0.54\pm 0.27$	$30.12\pm 30.58$
ISO39	$0.59\pm 0.28$	$0.62\pm 0.30$	$0.93\pm 0.15$	$0.69\pm 0.28$	$18.91\pm 29.11$	$0.55\pm 0.26$	$0.61\pm 0.28$	$0.87\pm 0.21$	$0.67\pm 0.25$	$16.34\pm 14.52$
SBGFRLS40	$0.72\pm 0.22$	$0.73\pm 0.22$	$0.98\pm 0.04$	$0.81\pm 0.18$	$9.48\pm 9.66$	$0.68\pm 0.25$	$0.73\pm 0.26$	$\mathbf{0.90}\pm \mathbf{0.15}$	$0.78\pm 0.21$	$14.13\pm 13.02$
IVW33	$0.68\pm 0.18$	$0.74\pm 0.20$	$0.94\pm 0.14$	$0.80\pm 0.15$	$6.53\pm 5.55$	$0.70\pm 0.19$	$0.86\pm 0.16$	$0.82\pm 0.21$	$0.81\pm 0.16$	$6.94\pm \mathbf{6.55}$
MOW34	$0.74\pm 0.20$	$0.79\pm 0.20$	$0.93\pm 0.13$	$0.83\pm 0.16$	$6.22\pm 6.01$	$0.72\pm 0.21$	$\mathbf{0.90}\pm 0.17$	$0.80\pm 0.20$	$0.82\pm 0.17$	$6.90\pm 6.97$
RACM35	$0.63\pm 0.19$	$0.82\pm 0.21$	$0.77\pm 0.19$	$0.75\pm 0.16$	$7.82\pm 6.09$	$0.63\pm \mathbf{0.18}$	$0.89\pm 0.18$	$0.71\pm 0.19$	$0.76\pm 0.16$	$8.08\pm 6.65$
mRLS41	$0.53\pm \mathbf{0}.\mathbf{17}$	$\mathbf{0.83}\pm \mathbf{0}.\mathbf{17}$	$0.64\pm 0.23$	$0.67\pm 0.15$	$10.02\pm 6.65$	$0.51\pm 0.20$	$\mathbf{0.90}\pm \mathbf{0.12}$	$0.56\pm 0.24$	$0.65\pm 0.18$	$10.93\pm 7.33$
CNN42	$0.62\pm 0.25$	$0.74\pm 0.30$	$0.82\pm 0.14$	$0.73\pm 0.22$	$16.41\pm 22.09$	$0.66\pm 0.24$	$0.80\pm 0.26$	$0.83\pm 0.18$	$0.77\pm 0.20$	$11.74\pm 14.51$
Ours	$\mathbf{0.78}\pm \mathbf{0.17}$	$0.79\pm \mathbf{0.17}$	$\mathbf{0.99}\pm \mathbf{0.03}$	$\mathbf{0.87}\pm \mathbf{0.13}$	$\mathbf{4.07}\pm \mathbf{2.76}$	$\mathbf{0.83}\pm 0.24$	$0.89\pm 0.20$	$\mathbf{0.90}\pm 0.20$	$\mathbf{0.88}\pm \mathbf{0.20}$	$\mathbf{4.85}\pm 7.28$

Note: Bold numbers indicate the best performance.