
Proceedings Paper
Limited view angle iterative CT reconstructionFormat | Member Price | Non-Member Price |
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Paper Abstract
Computed Tomography (CT) is widely used for transportation security to screen baggage for potential threats.
For example, many airports use X-ray CT to scan the checked baggage of airline passengers. The resulting
reconstructions are then used for both automated and human detection of threats. Recently, there has been
growing interest in the use of model-based reconstruction techniques for application in CT security systems.
Model-based reconstruction offers a number of potential advantages over more traditional direct reconstruction
such as filtered backprojection (FBP). Perhaps one of the greatest advantages is the potential to reduce reconstruction
artifacts when non-traditional scan geometries are used. For example, FBP tends to produce very
severe streaking artifacts when applied to limited view data, which can adversely affect subsequent processing
such as segmentation and detection.
In this paper, we investigate the use of model-based reconstruction in conjunction with limited-view scanning
architectures, and we illustrate the value of these methods using transportation security examples. The advantage
of limited view architectures is that it has the potential to reduce the cost and complexity of a scanning system,
but its disadvantage is that limited-view data can result in structured artifacts in reconstructed images. Our
method of reconstruction depends on the formulation of both a forward projection model for the system, and a
prior model that accounts for the contents and densities of typical baggage. In order to evaluate our new method,
we use realistic models of baggage with randomly inserted simple simulated objects. Using this approach, we
show that model-based reconstruction can substantially reduce artifacts and improve important metrics of image
quality such as the accuracy of the estimated CT numbers.
Paper Details
Date Published: 10 February 2012
PDF: 9 pages
Proc. SPIE 8296, Computational Imaging X, 82960F (10 February 2012); doi: 10.1117/12.917781
Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)
PDF: 9 pages
Proc. SPIE 8296, Computational Imaging X, 82960F (10 February 2012); doi: 10.1117/12.917781
Show Author Affiliations
Sherman J. Kisner, Purdue Univ. (United States)
Eri Haneda, Purdue Univ. (United States)
Charles A. Bouman, Purdue Univ. (United States)
Eri Haneda, Purdue Univ. (United States)
Charles A. Bouman, Purdue Univ. (United States)
Sondre Skatter, Morpho Detection, Inc. (United States)
Mikhail Kourinny, Morpho Detection, Inc. (United States)
Simon Bedford, Astrophysics, Inc. (United States)
Mikhail Kourinny, Morpho Detection, Inc. (United States)
Simon Bedford, Astrophysics, Inc. (United States)
Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)
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