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Proceedings Paper

Reconstruction of electron paramagnetic resonance images using iterative methods
Author(s): Delia P. McGarry; John Cook; Sankaran Subramanian; Nallathamby Devasahayam; Murali Krishna Cherukuri; Calvin A. Johnson
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Paper Abstract

Electron Paramagnetic Resonance (EPR) allows for the non-invasive imaging of free radicals in biological systems. Although a number of physical factors have hindered the development of EPR as an imaging modality, EPR offers the potential for tissue oxymetry. EPR images are typically reconstructed using a traditional filtered back-projection technique. We are attempting to improve the quality of EPR images by using maximum-entropy based iterative image reconstruction algorithms. Our investigation has so far focused on two methods, the multiplicative algebraic reconstruction technique (MART), and an algorithm that is motivated by interior-point reconstruction. MART is a row-action method that maintains strict equality in the constraints while minimizing the entropy functional. The latter method, which we have named Least-Squares Barrier Entropy (LSBEnt), transforms the constrained problem into an unconstrained problem and maximizes entropy at a prescribed distance from the measured data. EPR studies are frequently characterized by low signal-to-noise ratios and wide line widths. The effect of the backprojection streaking artifact can be quite severe and can seriously compromise a study. We have compared the iterative results with filtered backprojection on two-dimensional (2-D) EPR acquisitions of various phantoms. Encouraging preliminary results have demonstrated that one of the clear advantages of the iterative methods is their lack of streaking artifacts that plague filtered backprojection.

Paper Details

Date Published: 3 July 2001
PDF: 6 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431097
Show Author Affiliations
Delia P. McGarry, National Institutes of Health (United States)
John Cook, National Institutes of Health (United States)
Sankaran Subramanian, National Institutes of Health (United States)
Nallathamby Devasahayam, National Institutes of Health (United States)
Murali Krishna Cherukuri, National Institutes of Health (United States)
Calvin A. Johnson, National Institutes of Health (United States)

Published in SPIE Proceedings Vol. 4322:
Medical Imaging 2001: Image Processing
Milan Sonka; Kenneth M. Hanson, Editor(s)

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