Table 2.

Performance comparison with state-of-the-art semi-supervised segmentation methods on the MoNuSeg dataset

Label	Method	DSC (%)	IoU (%)	Precision (%)	Recall (%)	F1-score (%)
1/16	MT [29]	71.03	55.68	69.34	76.24	72.71
	UA-MT [30]	72.08	57.20	67.82	81.11	73.87
	MMS [32]	72.64	56.71	64.84	83.78	73.10
	Our method	74.04	59.12	70.92	78.52	74.53
1/8	MT [29]	72.52	57.48	71.31	76.95	73.77
	UA-MT [30]	74.48	59.90	69.19	83.91	75.84
	MMS [32]	75.35	60.25	72.19	80.10	75.94
	Our method	76.06	61.73	73.14	80.25	76.53
1/4	MT [29]	74.32	59.48	72.41	78.00	75.10
	UA-MT [30]	76.18	61.80	75.98	78.69	77.31
	MMS [32]	76.33	61.30	74.00	78.23	76.06
	Our method	78.92	65.44	77.80	80.90	79.32
100%	FullSup	79.27	65.90	75.06	84.54	79.52

Values in bold indicate the best experimental results