Abstract
Wavelet transform is widely used in feature extraction of magnetic resonance imaging. However, the traditional discrete wavelet transform (DWT) suffers from translation variant property, which may extract significantly different features from two images of the same subject with only slight movement. In order to solve this problem, this paper utilizes stationary wavelet transform (SWT) to extract features instead of DWT. Experiments on a normal brain MRI demonstrate that wavelet coefficients via SWT is superior to that via DWT concerning translation invariant property.
| Original language | English |
|---|---|
| Title of host publication | 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 |
| DOIs | |
| Publication status | Published - 2010 |
| Externally published | Yes |
| Event | 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 - Wuhan, China Duration: 23 Apr 2010 → 25 Apr 2010 |
Publication series
| Name | 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 |
|---|
Conference
| Conference | 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 |
|---|---|
| Country/Territory | China |
| City | Wuhan |
| Period | 23/04/10 → 25/04/10 |
Keywords
- Discrete wavelet transform
- Feature extraction
- Magnetic resonance imaging
- Stationary wavelet transform
- Translation invariance
Fingerprint
Dive into the research topics of 'Feature extraction of brain MRI by stationary wavelet transform'. Together they form a unique fingerprint.Cite this
Zhang, Y., Dong, Z., Wu, L., Wang, S., & Zhou, Z. (2010). Feature extraction of brain MRI by stationary wavelet transform. In 2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 Article 5462491 (2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010). https://doi.org/10.1109/ICBECS.2010.5462491