9 citations · 13 across the 4 of their papers we have counts for
9 papers
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…
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…
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…
Maximum Likelihood Estimation of Head Motion using Epipolar Consistency
Alexander Preuhs, Nishant Ravikumar, Michael Manhart +5
Open gantry C-arm systems that are placed within the interventional room enable 3-D imaging and guidance for stroke therapy without patient transfer. This can profit in drastically…