137 citations · 841 across the 28 of their papers we have counts for
28 papers
Robustness Investigation on Deep Learning CT Reconstruction for Real-Time Dose Optimization
Chang Liu, Yixing Huang, Joscha Maier +3
In computed tomography (CT), automatic exposure control (AEC) is frequently used to reduce radiation dose exposure to patients. For organ-specific AEC, a preliminary CT reconstruct…
Deep Learning-Based Reconstruction of Interventional Tools from Four X-Ray Projections for Tomographic Interventional Guidance
Elias Eulig, Joscha Maier, Michael Knaup +4
Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a C-arm system. However, the projective data provide only limited in…
Searching for primordial helical magnetic fields
M. Kachelriess, B. C. Martinez
The presence of non-zero helicity in intergalactic magnetic fields (IGMF) has been suggested as a clear signature for their primordial origin. We extend a previous analysis of diff…
Neural Networks-based Regularization for Large-Scale Medical Image Reconstruction
Andreas Kofler, Markus Haltmeier, Tobias Schaeffter +4
In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction. Recently, Deep Lear…
Towards Automatic Abdominal Multi-Organ Segmentation in Dual Energy CT using Cascaded 3D Fully Convolutional Network
Shuqing Chen, Holger Roth, Sabrina Dorn +7
Automatic multi-organ segmentation of the dual energy computed tomography (DECT) data can be beneficial for biomedical research and clinical applications. However, it is a challeng…
X-ray tomographic intervention guidance: Towards real-time 4D imaging
Sönke Bartling, Marc Kachelrieß
Implementation of real-time, continuous, and three-dimensional imaging (4D intervention guidance) would be a quantum leap for minimally-invasive medicine. It allows guidance during…