Tradeoff between noise properties and local impulse response in statistical prior image constrained compressed sensing

Pascal Thériault Lauzier; Yinsheng Li; Guang-Hong Chen

doi:10.1117/12.2007935

19 March 2013 Tradeoff between noise properties and local impulse response in statistical prior image constrained compressed sensing

Pascal Thériault Lauzier, Yinsheng Li, Guang-Hong Chen

Author Affiliations +

Proceedings Volume 8668, Medical Imaging 2013: Physics of Medical Imaging; 86681K (2013) https://doi.org/10.1117/12.2007935
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

The increase in the use of CT scanning in the clinical setting is raising concerns from the medical community. In order to reduce the dose of ionizing radiation imparted to patients during CT scans, statistical image recon struction was proposed. This family of algorithm aims at improving image noise characteristics by modeling the stochastic x-ray detection process in the reconstruction algorithm. It was shown however that statistical recon struction may lead to an anisotropic spatial resolution. In this abstract, we study this tradeoff in the context of a statistical formulation of the dose reduction using prior image constrained compressed sensing framework (DR-PICCS). Two numerically-simulated phantoms and a dataset acquired in vivo were used for this evaluation. It is demonstrated that the inclusion of a statistical model in DR-PICCS may whiten the NPS and uniformize the noise spatial distribution in the image. However, the images may suffer from an anisotropic spatial resolution while the images reconstructed using DR-PICCS without statistical model have more isotropic spatial resolution. Due to the flexibility offered in PICCS, a specially-designed prior image processing method has been used in statistical DR-PICCS to palliate for the anisotropy in spatial resolution.

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Pascal Thériault Lauzier, Yinsheng Li, and Guang-Hong Chen "Tradeoff between noise properties and local impulse response in statistical prior image constrained compressed sensing", Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86681K (19 March 2013); https://doi.org/10.1117/12.2007935

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KEYWORDS

Point spread functions

Spatial resolution

Statistical analysis

Reconstruction algorithms

CT reconstruction

Compressed sensing

Diffusion

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