Feature extraction of brain MRI by stationary wavelet transform

Yudong Zhang*, Zhengchao Dong, Lenan Wu, Shuihua Wang, Zhenyu Zhou

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

21 Citations (Scopus)

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 languageEnglish
Title of host publication2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010 - Wuhan, China
Duration: 23 Apr 201025 Apr 2010

Publication series

Name2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

Conference

Conference2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010
Country/TerritoryChina
CityWuhan
Period23/04/1025/04/10

Keywords

  • Discrete wavelet transform
  • Feature extraction
  • Magnetic resonance imaging
  • Stationary wavelet transform
  • Translation invariance

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