A Regularization Method Based on the Correlations of Diffusion Weighted Images

Author

Yi Sanli ; Chen Zhencheng ; Ling Hongli ; Jiang pei ; Li Weng

Author_Institution

Biomed. Eng. Inst., Central South Univ., Changsha, China

fYear

2009

fDate

17-19 Oct. 2009

Firstpage

1

Lastpage

5

Abstract

Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of DTI data. The method we present in this thesis works for the regularization of DTI data, which takes into account all the relations of DWI components, including relations of the values at different encoding directions. Our method is based on the theory of Wiener filter, and we molded it to filter the DWI dataset The method was illustrated by the synthetic and real data and the result has supported the filtering methodology proposed in this thesis.

Keywords

biomedical MRI; correlation methods; filtering theory; image coding; medical image processing; MR images; Wiener filter theory; diffusion tensor imaging; diffusion weighted images; encoding; filtering methodology; regularization method; Biomedical computing; Biomedical engineering; Diffusion tensor imaging; Encoding; Filtering theory; Image analysis; Rician channels; Smoothing methods; Tensile stress; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-4132-7

Electronic_ISBN

978-1-4244-4134-1

Type

conf

DOI

10.1109/BMEI.2009.5304865

Filename

5304865