A Regularization Method Based on the Correlations of Diffusion Weighted Images

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...

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Hauptverfasser: Yi Sanli, Chen Zhencheng, Ling Hongli, Jiang Pei, Li Weng
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creator Yi Sanli
Chen Zhencheng
Ling Hongli
Jiang Pei
Li Weng
description 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.
doi_str_mv 10.1109/BMEI.2009.5304865
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subjects Biomedical computing
Biomedical engineering
Diffusion tensor imaging
Encoding
Filtering theory
Image analysis
Rician channels
Smoothing methods
Tensile stress
Wiener filter
title A Regularization Method Based on the Correlations of Diffusion Weighted Images
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