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Investigative Radiology|June 28, 2023
Computed Tomography 2.0: New Detector Technology, AI, and Other DevelopmentsMichael Lell, Marc KachelrießMedical Physics|February 6, 2015
Dual energy CT: how well can pseudo-monochromatic imaging reduce metal artifacts?Stefan Kuchenbecker, Sebastian Faby, Stefan Sawall, et al.Medical Physics|April 10, 2012
Frequency split metal artifact reduction (FSMAR) in computed tomographyEsther Meyer, Rainer Raupach, Michael Lell, et al.Medical Physics|February 14, 2024
Training of a deep learning based digital subtraction angiography method using synthetic dataLizhen Duan, Elias Eulig, Michael Knaup, et al.Scientific Reports|April 23, 2024
Two-view topogram-based anatomy-guided CT reconstruction for prospective risk minimizationChang Liu, Laura Klein, Yixing Huang, et al.Medical Physics|December 10, 2019
Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networksShuqing Chen, Xia Zhong, Shiyang Hu, et al.Medical Physics|July 3, 2015
Performance of today's dual energy CT and future multi energy CT in virtual non-contrast imaging and in iodine quantification: A simulation studySebastian Faby, Stefan Kuchenbecker, Stefan Sawall, et al.Medical Physics|July 3, 2016
An efficient computational approach to model statistical correlations in photon counting x-ray detectorsSebastian Faby, Joscha Maier, Stefan Sawall, et al.Radiologie (Heidelberg, Germany)|June 12, 2023
[Risk-minimizing tube current modulation for computed tomography]Marc KachelrießMedical Physics|May 7, 2021
Deep learning-based coronary artery motion estimation and compensation for short-scan cardiac CTJoscha Maier, Sergej Lebedev, Julien Erath, et al.Pageof 20