Segmentation of medical images based on dyadic wavelet transform and active contour model.
- Author:
Hong LI
1
;
Huinan WANG
;
Linfeng CHANG
;
Xiaoli SHAO
Author Information
1. College of Automation Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China. lihonglilan@yahoo.com.cn
- Publication Type:Journal Article
- MeSH:
Algorithms;
Brain;
anatomy & histology;
Humans;
Image Enhancement;
Image Interpretation, Computer-Assisted;
methods;
Magnetic Resonance Imaging;
Pattern Recognition, Automated;
methods
- From:
Journal of Biomedical Engineering
2008;25(6):1276-1281
- CountryChina
- Language:Chinese
-
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.
