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3 October 2014 Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography
Emil Y. Sidky, David N. Kraemer, Erin G. Roth, Christer Ullberg, Ingrid S. Reiser, Xiaochuan Pan
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Funded by: NSF MedIX REU Program, NIH, NIH R01
Journal of Medical Imaging, Vol. 1, Issue 3, 031007 (October 2014). https://doi.org/10.1117/1.JMI.1.3.031007
Abstract
One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Emil Y. Sidky, David N. Kraemer, Erin G. Roth, Christer Ullberg, Ingrid S. Reiser, and Xiaochuan Pan "Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography," Journal of Medical Imaging 1(3), 031007 (3 October 2014). https://doi.org/10.1117/1.JMI.1.3.031007
Published: 3 October 2014
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Cited by 36 scholarly publications and 5 patents.
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KEYWORDS
X-ray computed tomography
Image restoration
Reconstruction algorithms
Algorithm development
CT reconstruction
Data modeling
Image filtering
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