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29 April 2005 A new reconstruction algorithm for energy-resolved coherent scatter computed tomography
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For the first time, a reconstruction technique based on filtered back-projection (FBP) using curved 3D back-projection lines is applied to energy-resolved coherent-scatter projection data. Coherent-scatter computed tomography (CSCT) yields information about the molecular structure of an object. It has been shown that the relatively poor spectral resolution due to the application of a polychromatic X-ray source can be overcome, when energy-resolved detection is used. So far, the energy-resolved projection data, acquired with a CSCT scanner, are reconstructed with the help of algebraic reconstruction techniques (ART). Due to the computational complexity of iterative reconstruction, these methods lead to relatively long reconstruction times. In this contribution, a reconstruction algorithm based on 3D FBP is introduced and applied to projection data acquired with a demonstrator setup similar to a multi-line CT scanner geometry using an energy-resolving CdTe-detector. Within a fraction of the computation time of algebraic reconstruction methods, an image of comparable quality is generated when using FBP reconstruction. In addition, the FBP approach has the advantage, that sub-field-of-view reconstruction becomes feasible. This allows a selective reconstruction of the scatter function for a region of interest. The method is based on a high-pass filtering of the scatter data in fan-beam direction applied to all energy channels. The 3D back-projection is performed along curved lines through a volume defined by the in-plane spatial coordinates and the wave-vector transfer.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Udo van Stevendaal, Jens-Peter Schlomka, Axel Thran, Johannes Delfs, and Hans Barschdorf "A new reconstruction algorithm for energy-resolved coherent scatter computed tomography", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005);

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