Wavelet shrinkage in tomography

Author

Kolaczyk, Eric D.

Author_Institution

Dept. of Stat., Chicago Univ., IL, USA

fYear

1994

fDate

1994

Firstpage

1206

Abstract

We use wavelet shrinkage methods to reconstruct images from tomographic data. Within the framework of Donoho´s wavelet-vaguelette decomposition, we create a multiresolution analogue of the traditional filtering of backprojected projections approach to compute the empirical wavelet coefficients in an efficient manner. Level-dependent thresholds are used in shrinking these coefficients to accommodate the ill-posedness of the problem. Inversion of the result yields a denoised reconstruction of the underlying image with respect to a 2D wavelet basis

Keywords

computerised tomography; 2D wavelet basis; Donoho wavelet-vaguelette decomposition; backprojected projections; denoised reconstruction; empirical wavelet coefficients; filtering; image reconstruction; inversion; level-dependent thresholds; multiresolution analogue; positron emission tomography; tomographic data; tomography; wavelet shrinkage; Analog computers; Filtering; Gaussian noise; Image reconstruction; Minimax techniques; Noise level; Statistics; Tomography; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE

Conference_Location

Baltimore, MD

Print_ISBN

0-7803-2050-6

Type

conf

DOI

10.1109/IEMBS.1994.415395

Filename

415395