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Proceedings Paper

Statistical noise reduction with projection space multiscale decomposition and penalized weighted least square
Author(s): Shaojie Tang; Yi Yang; Xiangyang Tang
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Paper Abstract

A statistical noise reduction approach is proposed for x-ray computed tomography imaging. The isotropic diffusion partial differential equation is derived from image space to projection space in the equi-angular fan-beam geometry and then used to obtain a projection space multi-scale decomposition by iteratively approximating a Gaussian convolution kernel function with an expected variance. Subsequently, the penalized weighted least square methods with three different objective functions are developed and implemented to reduce quantum noise in the projection data. Experimental results of computer simulated projection data have demonstrated the performance of the proposed approach.

Paper Details

Date Published: 3 March 2012
PDF: 12 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83133G (3 March 2012); doi: 10.1117/12.911122
Show Author Affiliations
Shaojie Tang, Emory Univ. School of Medicine (United States)
Yi Yang, Emory Univ. School of Medicine (United States)
Xiangyang Tang, Emory Univ. School of Medicine (United States)


Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)

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