Table 3.

Performance comparison of RG with MAKM and U-Net for 12 randomly selected brain images from BRATS2015 Dataset.

Metric	Algorithm	im081	im274	im473	im551	im06	im973	im689	im792	im1507	im781	im733	im1238	Avg
	RG	99.6	99.8	97.4	99.6	99.6	99.7	100.0	99.1	98.7	99.2	99.7	96.8	99.1
Acc (%)	MAKM	84.9	89.1	97.2	95.9	85.4	79.7	76.9	87.7	84.3	95.6	90.4	84.6	87.6
	U-NET	99.8	99.8	93.3	99.8	99.8	98.7	99.8	89.2	99.5	99.5	99.1	86.6	97.1
	RG	0.91	0.92	0.62	0.92	0.92	0.94	0.89	0.77	0.80	0.88	0.85	0.47	0.82
IoU	MAKM	0.05	0.01	0.61	0.50	0.23	0.02	0.02	0.23	0.29	0.58	0.04	0.28	0.24
	U-NET	0.95	0.93	0.39	0.94	0.95	0.76	0.61	0.25	0.92	0.93	0.45	0.31	0.70
	RG	0.95	0.96	0.76	0.96	0.96	0.97	0.94	0.87	0.89	0.94	0.92	0.64	0.90
DSS	MAKM	0.09	0.01	0.75	0.67	0.38	0.03	0.03	0.37	0.44	0.74	0.09	0.44	0.34
	U-NET	0.98	0.96	0.56	0.97	0.97	0.86	0.76	0.40	0.96	0.96	0.62	0.47	0.79
	RG	95.3	93.9	83.5	92.1	94.5	96.2	92.2	82.0	79.8	91.2	92.9	46.8	86.7
Sn (%)	MAKM	18.2	3.5	89.1	99.3	100.0	7.4	100.0	96.9	99.4	99.9	25.8	98.5	69.8
	U-NET	98.9	97.7	85.7	98.0	98.8	97.2	60.9	98.3	92.9	95.4	45.2	99.9	89.1
	RG	99.8	100.0	98.2	100.0	99.9	99.9	100.0	99.8	100.0	99.8	99.8	100.0	99.7
Sp (%)	MAKM	87.9	90.9	97.6	95.7	84.7	82.9	76.8	87.4	83.3	95.3	91.6	83.7	88.2
	U-NET	99.8	99.9	93.7	99.8	99.8	98.8	100.0	88.9	99.9	99.8	100.0	85.8	97.2
	RG	0.05	0.02	0.35	0.01	0.03	0.02	0.03	0.06	0.00	0.03	0.09	0.00	0.06
EF	MAKM	0.18	0.03	0.89	0.99	1.00	0.07	1.00	0.97	0.99	1.00	0.26	0.98	0.70
	U-NET	0.99	0.98	0.86	0.98	0.99	0.97	0.61	0.98	0.93	0.95	0.45	1.00	0.89
	RG	0.95	0.94	0.83	0.92	0.94	0.96	0.92	0.82	0.80	0.91	0.93	0.47	0.87
OF	MAKM	0.18	0.03	0.89	0.99	1.00	0.07	1.00	0.97	0.99	1.00	0.26	0.98	0.70
	U-NET	0.99	0.98	0.86	0.98	0.99	0.97	0.61	0.98	0.93	0.95	0.45	1.00	0.89
	RG	165.52	174.19	147.51	167.26	166.43	170.25	188.41	157.89	154.39	159.74	169.80	145.23	163.89
PNSR	MAKM	129.72	132.99	146.42	142.69	130.06	126.75	125.49	131.81	129.36	142.02	134.30	129.55	133.43
	U-NET	172.31	175.68	137.87	170.98	171.49	154.11	175.68	133.12	163.80	164.69	157.43	130.96	159.01