Statistical image reconstruction for polyenergetic X-ray computed tomography
University of Michigan–Ann Arbor
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Abstract
This paper describes a statistical image reconstruction method for X-ray computed tomography (CT) that is based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. We assume that the object consists of a given number of nonoverlapping materials, such as soft tissue and bone. The attenuation coefficient of each voxel is the product of its unknown density and a known energy-dependent mass attenuation coefficient. We formulate a penalized-likelihood function for this polyenergetic model and develop an ordered-subsets iterative algorithm for estimating the unknown densities in each voxel. The algorithm…
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2Topics & keywords
Topics
Keywords
- Voxel
- Iterative reconstruction
- Attenuation
- Attenuation coefficient
- Tomography
- Iterative method
- Energy (signal processing)
- Computer science
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