Research Article
Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification
Table 3
Values of memberships and clustering centers (
and
) in the neighborhood shown in Figure
7(b) after 1, 4, and 7 iterations.
(a) After 1 iteration |
| 0.6007 | | 0.5507 | | 0.5677 | 0.5236 | | 0.5712 | | 0.5178 | 0.5807 | | 0.5008 | | 0.5438 | | | | | |
| 0.4922 | | 0.4993 | | 0.4892 | 0.5934 | | 0.4993 | | 0.5372 | 0.4993 | | 0.4898 | | 0.5192 | | | | | |
|
|
(b) After 4 iterations |
| 0.3446 | | 0.3247 | | 0.3251 | 0.4024 | | 0.3512 | | 0.3415 | 0.3515 | | 0.3861 | | 0.3488 | | | | | |
| 0.2452 | | 0.3412 | | 0.2944 | 0.3544 | | 0.2586 | | 0.3589 | 0.2881 | | 0.3245 | | 0.2292 | | | | | |
|
|
(c) After 7 iterations |
| 0.0278 | | 0.0852 | | 0.0353 | 0.0267 | | 0.0497 | | 0.0318 | 0.0795 | | 0.0278 | | 0.0519 | | | | | |
| 0.0105 | | 0.0084 | | 0.0068 | 0.0097 | | 0.0092 | | 0.0087 | 0.0082 | | 0.0081 | | 0.0051 | | | | | |
|
|