Paper
3 July 2001 Reconstruction of electron paramagnetic resonance images using iterative methods
Delia P. McGarry, John Cook, Sankaran Subramanian, Nallathamby Devasahayam, Murali Krishna Cherukuri, Calvin A. Johnson
Author Affiliations +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Delia P. McGarry, John Cook, Sankaran Subramanian, Nallathamby Devasahayam, Murali Krishna Cherukuri, and Calvin A. Johnson "Reconstruction of electron paramagnetic resonance images using iterative methods", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431097
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KEYWORDS
Reconstruction algorithms

Iterative methods

Signal to noise ratio

Distance measurement

Magnetism

Imaging systems

Image restoration

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