An algorithm based on deformable contour models for medical image segmentation / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 717-721, 2006.
Article
in Zh
| WPRIM
| ID: wpr-249519
Responsible library:
WPRO
ABSTRACT
This paper provides a new medical image segmentation algorithm using a deformable contour model, which integrates Fuzzy C-Means(FCM) Clustering technique and deformable contour model. An external fuzzy constrain is defined from the membership function value of FCM, which joins the external constrain of the deformable model and drives the deformable model towards the contour ideal edge of the object. Examples are presented to demonstrate the efficiency and feasibility of the approach on spinal MRI images and the results are encouraging.
Full text:
1
Index:
WPRIM
Main subject:
Spine
/
Algorithms
/
Image Processing, Computer-Assisted
/
Pattern Recognition, Automated
/
Magnetic Resonance Imaging
/
Cluster Analysis
/
Fuzzy Logic
/
Methods
Type of study:
Prognostic_studies
Limits:
Humans
Language:
Zh
Journal:
Journal of Biomedical Engineering
Year:
2006
Type:
Article