147 citations · 306 across the 13 of their papers we have counts for
6 papers · 1 filter
Deep autofocus with cone-beam CT consistency constraint
Alexander Preuhs, Michael Manhart, Philipp Roser +5
High quality reconstruction with interventional C-arm cone-beam computed tomography (CBCT) requires exact geometry information. If the geometry information is corrupted, e. g., by…
Image Quality Assessment for Rigid Motion Compensation
Alexander Preuhs, Michael Manhart, Philipp Roser +5
Diagnostic stroke imaging with C-arm cone-beam computed tomography (CBCT) enables reduction of time-to-therapy for endovascular procedures. However, the prolonged acquisition time…
Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging
Bernhard Stimpel, Christopher Syben, Tobias Würfl +4
Hybrid X-ray and magnetic resonance (MR) imaging promises large potential in interventional medical imaging applications due to the broad variety of contrast of MRI combined with f…
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
Bernhard Stimpel, Christopher Syben, Franziska Schirrmacher +3
Deep learning-based image processing is capable of creating highly appealing results. However, it is still widely considered as a "blackbox" transformation. In medical imaging, thi…
Learning with Known Operators reduces Maximum Training Error Bounds
Andreas K. Maier, Christopher Syben, Bernhard Stimpel +7
We describe an approach for incorporating prior knowledge into machine learning algorithms. We aim at applications in physics and signal processing in which we know that certain op…
PYRO-NN: Python Reconstruction Operators in Neural Networks
Christopher Syben, Markus Michen, Bernhard Stimpel +3
Purpose: Recently, several attempts were conducted to transfer deep learning to medical image reconstruction. An increasingly number of publications follow the concept of embedding…