Prior image constrained compressed sensing: a quantitative performance evaluation

Pascal Thériault Lauzier; Jie Tang; Guang-Hong Chen

doi:10.1117/12.912138

3 March 2012 Prior image constrained compressed sensing: a quantitative performance evaluation

Pascal Thériault Lauzier, Jie Tang, Guang-Hong Chen

Author Affiliations +

Proceedings Volume 8313, Medical Imaging 2012: Physics of Medical Imaging; 83132F (2012) https://doi.org/10.1117/12.912138
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

The appeal of compressed sensing (CS) in the context of medical imaging is undeniable. In MRI, it could enable shorter acquisition times while in CT, it has the potential to reduce the ionizing radiation dose imparted to patients. However, images reconstructed using a CS-based approach often show an unusual texture and a potential loss in spatial resolution. The prior image constrained compressed sensing (PICCS) algorithm has been shown to enable accurate image reconstruction at lower levels of sampling. This study systematically evaluates an implementation of PICCS applied to myocardial perfusion imaging with respect to two parameters of its objective function. The prior image parameter α was shown here to yield an optimal image quality in the range 0.4 to 0.5. A quantitative evaluation in terms of temporal resolution, spatial resolution, noise level, noise texture, and reconstruction accuracy was performed.

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Pascal Thériault Lauzier, Jie Tang, and Guang-Hong Chen "Prior image constrained compressed sensing: a quantitative performance evaluation", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83132F (3 March 2012); https://doi.org/10.1117/12.912138

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