9 citations · 22 across the 12 of their papers we have counts for
6 papers · 1 filter
Routine Usage of AI-based Chest X-ray Reading Support in a Multi-site Medical Supply Center
Karsten Ridder, Alexander Preuhs, Axel Mertins +1
Research question: How can we establish an AI support for reading of chest X-rays in clinical routine and which benefits emerge for the clinicians and radiologists. Can it perform…
Appearance Learning for Image-based Motion Estimation in Tomography
Alexander Preuhs, Michael Manhart, Philipp Roser +5
In tomographic imaging, anatomical structures are reconstructed by applying a pseudo-inverse forward model to acquired signals. Geometric information within this process is usually…
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images
Yixing Huang, Alexander Preuhs, Michael Manhart +2
Image reconstruction from insufficient data is common in computed tomography (CT), e.g., image reconstruction from truncated data, limited-angle data and sparse-view data. Deep lea…
Field of View Extension in Computed Tomography Using Deep Learning Prior
Yixing Huang, Lei Gao, Alexander Preuhs +1
In computed tomography (CT), data truncation is a common problem. Images reconstructed by the standard filtered back-projection algorithm from truncated data suffer from cupping ar…
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…
Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior
Yixing Huang, Alexander Preuhs, Guenter Lauritsch +3
Robustness of deep learning methods for limited angle tomography is challenged by two major factors: a) due to insufficient training data the network may not generalize well to uns…