Paper
1 April 2016 Optimization-based reconstruction for reduction of CBCT artifact in IGRT
Dan Xia, Zheng Zhang, Pascal Paysan, Dieter Seghers, Marcus Brehm, Peter Munro, Emil Y. Sidky, Charles Pelizzari, Xiaochuan Pan
Author Affiliations +
Abstract
Kilo-voltage cone-beam computed tomography (CBCT) plays an important role in image guided radiation therapy (IGRT) by providing 3D spatial information of tumor potentially useful for optimizing treatment planning. In current IGRT CBCT system, reconstructed images obtained with analytic algorithms, such as FDK algorithm and its variants, may contain artifacts. In an attempt to compensate for the artifacts, we investigate optimization-based reconstruction algorithms such as the ASD-POCS algorithm for potentially reducing arti- facts in IGRT CBCT images. In this study, using data acquired with a physical phantom and a patient subject, we demonstrate that the ASD-POCS reconstruction can significantly reduce artifacts observed in clinical re- constructions. Moreover, patient images reconstructed by use of the ASD-POCS algorithm indicate a contrast level of soft-tissue improved over that of the clinical reconstruction. We have also performed reconstructions from sparse-view data, and observe that, for current clinical imaging conditions, ASD-POCS reconstructions from data collected at one half of the current clinical projection views appear to show image quality, in terms of spatial and soft-tissue-contrast resolution, higher than that of the corresponding clinical reconstructions.
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Dan Xia, Zheng Zhang, Pascal Paysan, Dieter Seghers, Marcus Brehm, Peter Munro, Emil Y. Sidky, Charles Pelizzari, and Xiaochuan Pan "Optimization-based reconstruction for reduction of CBCT artifact in IGRT", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97834B (1 April 2016); https://doi.org/10.1117/12.2217234
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KEYWORDS
Reconstruction algorithms

Imaging systems

Data modeling

Image restoration

CT reconstruction

Data acquisition

Image analysis

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