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Sebastian Faby

Researcher at German Cancer Research Center

Publications -  17
Citations -  385

Sebastian Faby is an academic researcher from German Cancer Research Center. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 4, co-authored 6 publications receiving 272 citations.

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Journal ArticleDOI

Performance of today’s dual energy CT and future multi energy CT in virtual non-contrast imaging and in iodine quantification: A simulation study

TL;DR: Comparing DECT with future MECT, the authors found noticeable material image quality improvements for an ideal photon counting detector; however, a realistic detector model with multiple energy bins predicts a performance on the level of dual source DECT at 100 kV/Sn 140 kV.
Journal ArticleDOI

Dual energy CT: how well can pseudo-monochromatic imaging reduce metal artifacts?

TL;DR: Pseudo-monochromatic imaging is able to reduce beam hardening, scatter, and metal artifacts in some cases but it cannot remove them, and raw data-based dual energy decomposition methods should be preferred, in particular, because the CNR penalty is almost negligible.
Journal ArticleDOI

An efficient computational approach to model statistical correlations in photon counting x-ray detectors.

TL;DR: An increment matrix approach describing the signal statistics of energy-selective photon counting detectors including spatial-spectral correlations between energy bins of neighboring detector pixels is introduced and evaluated and found to be of weak nature.
Journal ArticleDOI

Image quality and dose exposure of contrast-enhanced abdominal CT on a 1st generation clinical dual-source photon-counting detector CT in obese patients vs. a 2nd generation dual-source dual energy integrating detector CT.

TL;DR: In this paper , the authors compared the image quality of contrast-enhanced abdominal 1st-generation Photon-Counting Detector CT (PCD-CT) to a 2nd-generation Dual-Source Dual-Energy-Integrating-Detector (DSCT) in obese patients.
Proceedings ArticleDOI

CT calibration and dose minimization in image-based material decomposition with energy-selective detectors

TL;DR: In this article, the authors proposed an image-based method that determines optimal bin image weighting factors for material decomposition with respect to minimal material image noise, and showed that a perfect photon counting detector with four bins outperforms the dual energy CT technique by a noise reduction of 22% in the water image and 43% in an iodine image.