Dr. Fredrik Grönberg
at GE HealthCare
SPIE Involvement:
Author | Instructor
Publications (4)

Proceedings Article | 1 April 2024 Poster + Paper
Sara S. Tehrani, Karin Larsson, Fredrik Grönberg, Johannes Loberg, Hugo Linder, Mats Persson
Proceedings Volume 12925, 129252T (2024) https://doi.org/10.1117/12.3006727
KEYWORDS: Iodine, Computed tomography, Data modeling, Photon counting, Atherosclerosis, X-ray medical imaging, Spectral computed tomography

Proceedings Article | 15 February 2021 Poster + Presentation + Paper
Proceedings Volume 11595, 1159546 (2021) https://doi.org/10.1117/12.2581044
KEYWORDS: X-ray computed tomography, Image enhancement, Photon counting, Statistical modeling, Model-based design, Data modeling, Visual process modeling, Statistical analysis, Sensors, Optimization (mathematics)

SPIE Journal Paper | 15 October 2019
Joakim da Silva, Fredrik Grönberg, Björn Cederström, Mats Persson, Martin Sjölin, Zlatan Alagic, Robert Bujila, Mats Danielsson
JMI, Vol. 6, Issue 04, 043502, (October 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.4.043502
KEYWORDS: Sensors, Silicon, Prototyping, Modulation transfer functions, Photons, X-ray computed tomography, Scanners, Spatial resolution, Imaging systems, Image resolution

Proceedings Article | 9 March 2018 Presentation + Paper
Proceedings Volume 10573, 105730Z (2018) https://doi.org/10.1117/12.2293095
KEYWORDS: Monte Carlo methods, Photon counting, Statistical modeling, Computer simulations, Detector development, Statistical analysis

Course Instructor
SC1129: Photon Counting CT
This course explains the principles of photon counting detectors for spectral x-ray imaging. Typical technical implementations are described and fundamental differences to energy integrating systems are pointed out. In particular, the issues of high-rate handling and the effect of detector cross talk on energy resolution are described. Requirements on electronics for spectral imaging in computed tomography is also discussed. A second objective of the course is to describe how energy sensitive counting detectors make use of the energy sampling of the linear attenuation coefficients of the background and target materials for any given imaging task; methods like material basis decomposition and optimal energy weighting will be explained. The second objective highlights the interesting fact that while the spatial-frequency descriptor of signal-to-noise-ratio transfer (DQE) of a system gives a complete characterization of performance for energy integrating (and pure photon counting) systems, it fails to characterize multibin systems since a complete description of the transfer characteristics requires specification of how the information of each energy bin is handled. The latter is in turn dependent on the imaging case at hand which shows that there is no such thing as an imaging case independent system DQE for photon counting multibin systems. We also suggest how this issue could be resolved.
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