Research Article
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 | | | | | |
|
|