Regularization in Tomographic Reconstruction Using Thresholding Estimators

Abstract

In tomographic medical devices such as SPECT or PET cameras image reconstruction is an unstable inverse problem due to the presence of additive noise. A new family of regularization methods for reconstruction based on a thresholding procedure in wavelet and wavelet packet decompositions is studied. This approach is based on the fact that the decompositions provide a near-diagonalization of the inverse Radon transform and of the prior information on medical images. Corresponding algorithms have been developed for both 2-D and full 3-D reconstruction. These procedures are fast, non-iterative, flexible and their performances outperform Filtered Back-Projection and iterative procedures such as OS-EM.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409763

Entities

People

  • Andrew Laine
  • Jerome Kalifa
  • Peter D. Esser

Organizations

  • Columbia University Irving Medical Center

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Additives (Chemicals)
  • Algorithms
  • Biomedical Engineering
  • Computations
  • Decomposition
  • Engineering
  • Estimators
  • Frequency Domain
  • Inverse Problems
  • New York
  • Noise
  • Three Dimensional
  • Two Dimensional
  • Wavelet Transforms

Readers

  • Image Processing and Computer Vision.
  • Linear Algebra
  • Medical Imaging.