9 citations · 22 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
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…