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Proceedings Paper

Tomographic reconstruction with nonlinear diagonal estimators
Author(s): Jerome Kalifa; Andrew F. Laine; Peter D. Esser
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Paper Abstract

In tomographic reconstruction, the inversion of the Radon transform in the presence of noise is numerically unstable. Reconstruction estimators are studied where the regularization is performed by a thresholding in a wavelet or wavelet packet decomposition. These estimators are efficient and their optimality can be established when the decomposition provides a near-diagonalization of the inverse Radon transform operator and a compact representation of the object to be recovered. Several new estimators are investigated in different decomposition. First numerical results already exhibit a strong metrical and perceptual improvement over current reconstruction methods. These estimators are implemented with fast non-iterative algorithms, and are expected to outperform Filtered Back- Projection and iterative procedures for PET, SPECT and X-ray CT devices.

Paper Details

Date Published: 4 December 2000
PDF: 11 pages
Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); doi: 10.1117/12.408646
Show Author Affiliations
Jerome Kalifa, Columbia Univ. (United States)
Andrew F. Laine, Columbia Univ. (United States)
Peter D. Esser, Columbia-Presbyterian Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 4119:
Wavelet Applications in Signal and Image Processing VIII
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

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