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Journal of Medical Imaging • Open Access

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography
Author(s): Emil Y. Sidky; David N. Kraemer; Erin G. Roth; Christer Ullberg; Ingrid S. Reiser; Xiaochuan Pan

Paper 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.

Paper Details

Date Published: 3 October 2014
PDF: 16 pages
J. Med. Img. 1(3) 031007 doi: 10.1117/1.JMI.1.3.031007
Published in: Journal of Medical Imaging Volume 1, Issue 3
Show Author Affiliations
Emil Y. Sidky, The Univ. of Chicago Medical Ctr. (United States)
David N. Kraemer, The Univ. of Chicago Medical Ctr. (United States)
Erin G. Roth, The Univ. of Chicago Medical Ctr. (United States)
Christer Ullberg, XCounter AB (Sweden)
Ingrid S. Reiser, The Univ. of Chicago Medical Ctr. (United States)
Xiaochuan Pan, The Univ. of Chicago Medical Ctr. (United States)


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