Inhomogeneous magnetic resonance image segmentation by spatial model to fuzzy clustering
- VernacularTitle:基于模糊聚类空间模型的非均匀MR图像分割
- Author:
Bin LI
;
Wufan CHEN
- Publication Type:Journal Article
- Keywords:
image segmentation;
FCM clustering algorithm;
bias field correction;
spatial information of image
- From:
Chinese Medical Equipment Journal
1989;0(02):-
- CountryChina
- Language:Chinese
-
Abstract:
Fuzzy c-means (FCM) clustering algorithm is a popular model widely used in the segmentation of magnetic resonance image (MRI). The conventional FCM doesn't involve the spatial information of MRI and then unexpected segmentation results appear when it is applied to inhomogeneous MRI with noise and bias field. Modifying the objective function of FCM and introducing a variable as the parameter to control the tight degree of neighborhood effect present a spatial model to FCM clustering algorithm. The variable can reasonably use the spatial information of MRI. The experiment results show that the proposed algorithm can provide a powerful segmentation than the conventional FCM and others.
