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Proceedings Paper

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

Paper Details

Date Published: 19 March 2013
PDF: 7 pages
Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86681K (19 March 2013); doi: 10.1117/12.2007935
Show Author Affiliations
Pascal Thériault Lauzier, Univ. of Wisconsin-Madison (United States)
Yinsheng Li, Univ. of Wisconsin-Madison (United States)
Guang-Hong Chen, Univ. of Wisconsin-Madison (United States)


Published in SPIE Proceedings Vol. 8668:
Medical Imaging 2013: Physics of Medical Imaging
Robert M. Nishikawa; Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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