147 citations · 306 across the 13 of their papers we have counts for
14 papers
A comparative study between vision transformers and CNNs in digital pathology
Luca Deininger, Bernhard Stimpel, Anil Yuce +5
Recently, vision transformers were shown to be capable of outperforming convolutional neural networks when pretrained on sufficient amounts of data. In comparison to convolutional…
Fully-automatic CT data preparation for interventional X-ray skin dose simulation
Philipp Roser, Annette Birkhold, Alexander Preuhs +6
Recently, deep learning (DL) found its way to interventional X-ray skin dose estimation. While its performance was found to be acceptable, even more accurate results could be achie…
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…