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Gutjahr, R.; Polster, C.; Kappler, S.; Pietsch, H.; Jost, G.; Hahn, K.; Schöck, F.; Sedlmair, M.; Allmendinger, T.; Schmidt, B.; Krauss, B.; Flohr, T. G. (2016): Material Decomposition and Virtual Non-Contrast Imaging in Photon Counting Computed Tomography - An Animal Study. In: Kontos, Despina; Flohr, Thomas G. (eds.) : Medical Imaging 2016: Physics of Medical Imaging. Proceedings SPIE, Vol. 9783. SPIE.
Full text not available from 'Open Access LMU'.

Abstract

The energy resolving capabilities of Photon Counting Detectors (PCD) in Computed Tomography (CT) facilitate energy-sensitive measurements. The provided image-information can be processed with Dual Energy and Multi Energy algorithms. A research PCD-CT firstly allows acquiring images with a close to clinical configuration of both the X-ray tube and the CT-detector. In this study, two algorithms (Material Decomposition and Virtual Non-Contrast-imaging (VNC)) are applied on a data set acquired from an anesthetized rabbit scanned using the PCD-CT system. Two contrast agents (CA) are applied: A gadolinium (Gd) based CA used to enhance contrasts for vascular imaging, and xenon (Xe) and air as a CA used to evaluate local ventilation of the animal's lung. Four different images are generated: a) A VNC image, suppressing any traces of the injected Gd imitating a native scan, b) a VNC image with a Gd-image as an overlay, where contrast enhancements in the vascular system are highlighted using colored labels, c) another VNC image with a Xe-image as an overlay, and d) a 3D rendered image of the animal's lung, filled with Xe, indicating local ventilation characteristics. All images are generated from two images based on energy bin information. It is shown that a modified version of a commercially available dual energy software framework is capable of providing images with diagnostic value obtained from the research PCD-CT system.