Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

Table 2

Values of memberships and clustering centers ( and ) in the neighborhood shown in Figures 4(a) and 4(b) after 1, 4, and 7 iterations.

(a) After 1 iteration

0.4753		0.4727		0.4712
0.4717		0.4723		0.4753
0.4721		0.4736		0.4722
0.5031		0.5122		0.5124
0.5112		0.53031		0.5042
0.5121		0.5063		0.5066

(b) After 4 iterations

0.7564		0.7562		0.7601
0.7537		0.7523		0.7564
0.8120		0.7611		0.7589
0.7781		0.7881		0.7689
0.7833		0.7682		0.7596
0.7681		0.8195		0.7764

(c) After 7 iterations

0.9687		0.9311		0.9714
0.9658		0.9602		0.9596
0.9709		0.9673		0.9598
0.9868		0.9727		0.9943
0.9907		0.9739		0.9763
0.9960		0.9902		0.9856