Segmentation of medical images based on dyadic wavelet transform and active contour model / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1276-1281, 2008.
Article
in Chinese
| WPRIM
| ID: wpr-318169
ABSTRACT
The interference of noise and the weak edge characteristic of symptom information on medical images prevent the traditional methods of segmentation from having good effects. In this paper is proposed a boundary detection method of focus which is based on dyadic wavelet transform and active contour model. In this method, the true edge points are detected by dyadic wavelet transform and linked by improved fast active contour model algorithm. The result of experiment on MRI of brain shows that the method can remove the influence of noise effective and detect the contour of brain tumor actually.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Brain
/
Pattern Recognition, Automated
/
Magnetic Resonance Imaging
/
Image Interpretation, Computer-Assisted
/
Image Enhancement
/
Methods
Type of study:
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2008
Type:
Article
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