14 March 2007 Analytical cone-beam reconstruction using a multi-source inverse geometry CT system
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Abstract
In a 3rd generation CT system, a single source projects the entire field of view (FOV) onto a large detector opposite the source. In multi-source CT imaging, a multitude of sources sequentially project a part of the FOV on a much smaller detector. These sources may be distributed in both the trans-axial and axial directions in order to jointly cover the entire FOV. Scan data from multiple sources in the axial direction provide complementary information, which is not available in a conventional single-source CT system. In this work, an analytical 3D cone-beam reconstruction algorithm for multi-source CT is proposed. This approach has three distinctive features. First, multi-source data are re-binned transaxially to multiple offset third-generation datasets. Second, data points in sinograms from multiple source sets are either accepted or rejected for contribution to the backprojection of a given voxel. Third, instead of using a ramp filter, a Hilbert transform is combined with a parallel derivative to form the filtering mechanism. Phantom simulations are performed using a multi-source CT geometry and compared to conventional 3rd generation CT geometry. We show that multi-source CT can extend the axial scan coverage to 120mm without cone-beam artifacts, while a third-generation geometry results in compromised image quality at 60mm of axial coverage. Moreover, given that the cone-angle in the proposed geometry is limited to 7 degrees, there are no degrading effects such as the Heel effect and scattered radiation, unlike in a third-generation geometry with comparable coverage. An additional benefit is the uniform flux profile resulting in uniform image noise throughout the FOV and a uniform dose absorption profile.
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Zhye Yin, Zhye Yin, Bruno De Man, Bruno De Man, Jed Pack, Jed Pack, } "Analytical cone-beam reconstruction using a multi-source inverse geometry CT system", Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 651021 (14 March 2007); doi: 10.1117/12.712883; https://doi.org/10.1117/12.712883
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