Morphological Reconstruction-Based Image-Guided Fuzzy Clustering with a Novel Impact Factor

Table 3

The ASA of tested algorithms with various noises on Brain images.

Noise	FCM	FCM_S1	FCM_S2	FCM + G (ε = 0.1^4)	IFCM_GF (ρ)	FRFCM	MRIFCM_GF (ρ)
5% Rician	0.9993	0.9953	0.9908	0.9998	0.9999 (0.15)	0.9837	0.9952 (0.14)
10% Rician	0.8427	0.9866	0.9772	0.8480	0.9380 (0.15)	0.9762	0.9844 (0.1)
15% Rician	0.7075	0.9085	0.8313	0.7265	0.8167 (0.05)	0.9387	0.9483 (0.08)
20% Rician	0.6240	0.7993	0.7823	0.6456	0.7731 (0.03)	0.8984	0.9152 (0.08)
25% Rician	0.5540	0.7674	0.7477	0.5862	0.7410 (0.02)	0.8631	0.8745 (0.07)

The best segmentation accuracy among the group.