9 citations · 20 across the 9 of their papers we have counts for
11 papers
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning
Philipp Roser, Xia Zhong, Annette Birkhold +7
Scattered radiation is a major concern impacting X-ray image-guided procedures in two ways. First, back-scatter significantly contributes to patient (skin) dose during complicated…
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…
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…
Tenfold your photons -- a physically-sound approach to filtering-based variance reduction of Monte-Carlo-simulated dose distributions
Philipp Roser, Annette Birkhold, Alexander Preuhs +3
X-ray dose constantly gains interest in the interventional suite. With dose being generally difficult to monitor reliably, fast computational methods are desirable. A major drawbac…
Deep Scatter Splines: Learning-Based Medical X-ray Scatter Estimation Using B-splines
Philipp Roser, Annette Birkhold, Alexander Preuhs +5
The idea of replacing hardware by software to compensate for scattered radiation in flat-panel X-ray imaging is well established in the literature. Recently, deep-learningbased ima…