Inhomogeneous magnetic resonance image segmentation by spatial model to fuzzy clustering / 医疗卫生装备
Chinese Medical Equipment Journal
; (6)1989.
Article
in Zh
| WPRIM
| ID: wpr-585883
Responsible library:
WPRO
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.
Full text:
1
Index:
WPRIM
Type of study:
Prognostic_studies
Language:
Zh
Journal:
Chinese Medical Equipment Journal
Year:
1989
Type:
Article