Work

Maximum-likelihood calibration of an x-ray computed tomography system

Year: 2010

Type: conference-paper

Abstract: We present a maximum-likelihood (ML) method for calibrating the geometrical parameters of an x-ray computed tomography (CT) system. This method makes use of the full image data and not a reduced set of data. This algorithm is particularly useful for CT systems that change their geometry during the CT acquisition, such as an adaptive CT scan. Our ML search method uses a contracting-grid algorithm that does not require initial starting values to perform its estimate, thus avoiding problems associated with choosing initialization values.

DOI: 10.1109/nssmic.2010.5874262

Authors: J W Moore, R Van Holen, H H Barrett, L R Furenlid

Institutions: University of Arizona, Ghent University

Language: English

Topic: Advanced X-ray and CT Imaging

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Institute of Biomedical Imaging and Bioengineering

Awards: G1774695383, Center for Gamma-Ray Imaging

OpenAlex ID: W2129392987

FWCI:

Cites: 6

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Related to: 10