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Fast Feldkamp reconstruction based on focus of attention and distributed computing.

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Title: Fast Feldkamp reconstruction based on focus of attention and distributed computing.
Authors: Gregor, J.1 jgregor@cs.utk.edu, Gleason, S. S.2 paulusmj@imtekinc.com, Paulus, M. J.2 cates@sci.utah.edu, Cates, J.3 gleasons@imtekinc.com
Source: International Journal of Imaging Systems & Technology. Nov2002, Vol. 12 Issue 6, p229-234. 6p.
Subjects: Algorithms, Imaging systems, Image reconstruction, Geometric tomography, Computer programming, Computer science
Abstract: The Feldkamp algorithm is widely accepted as a practical conebeam reconstruction method for three-dimensional x-ray computed tomography. We introduce focus of attention, an effective and simple to implement datadriven preprocessing scheme, for identifying a convex subset of voxels that include all those relevant to the object under study. By concentrating on this subset of voxels during reconstruction, we reduce the computational demands of the Feldkamp algorithm correspondingly. To achieve further speed-up, all computations are distributed across a cluster of inexpensive, dual-processor PCs. We present experimental work based on mouse data obtained from the MicroCAT which is a high-resolution x-ray computed tomography system for small animal imaging. This work shows that focus of attention can cut the overall computation time in half without affecting the image quality. The method is general by nature and can easily be adapted to apply to other geometries and modalities as well as to iterative reconstruction algorithms. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 12, 229–234, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10027 [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Imaging Systems & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: The Feldkamp algorithm is widely accepted as a practical conebeam reconstruction method for three-dimensional x-ray computed tomography. We introduce focus of attention, an effective and simple to implement datadriven preprocessing scheme, for identifying a convex subset of voxels that include all those relevant to the object under study. By concentrating on this subset of voxels during reconstruction, we reduce the computational demands of the Feldkamp algorithm correspondingly. To achieve further speed-up, all computations are distributed across a cluster of inexpensive, dual-processor PCs. We present experimental work based on mouse data obtained from the MicroCAT which is a high-resolution x-ray computed tomography system for small animal imaging. This work shows that focus of attention can cut the overall computation time in half without affecting the image quality. The method is general by nature and can easily be adapted to apply to other geometries and modalities as well as to iterative reconstruction algorithms. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 12, 229–234, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10027 [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Imaging Systems & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Image reconstruction
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              Text: Nov2002
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