Search Results for author: Philipp Roser

Found 8 papers, 0 papers with code

X-ray Scatter Estimation Using Deep Splines

no code implementations22 Jan 2021 Philipp Roser, Annette Birkhold, Alexander Preuhs, Christopher Syben, Lina Felsner, Elisabeth Hoppe, Norbert Strobel, Markus Korwarschik, Rebecca Fahrig, Andreas Maier

Algorithmic X-ray scatter compensation is a desirable technique in flat-panel X-ray imaging and cone-beam computed tomography.

Medical Physics Image and Video Processing

2-D Respiration Navigation Framework for 3-D Continuous Cardiac Magnetic Resonance Imaging

no code implementations26 Dec 2020 Elisabeth Hoppe, Jens Wetzl, Philipp Roser, Lina Felsner, Alexander Preuhs, Andreas Maier

Continuous protocols for cardiac magnetic resonance imaging enable sampling of the cardiac anatomy simultaneously resolved into cardiac phases.

Anatomy

Cephalogram Synthesis and Landmark Detection in Dental Cone-Beam CT Systems

no code implementations9 Sep 2020 Yixing Huang, Fuxin Fan, Christopher Syben, Philipp Roser, Leonid Mill, Andreas Maier

The method trained on conventional cephalograms can be directly applied to landmark detection in the synthetic cephalograms, achieving 93. 0% and 80. 7% successful detection rate in 4 mm precision range for synthetic cephalograms from 3D volumes and 2D projections respectively.

3D Reconstruction Generative Adversarial Network +1

Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning

no code implementations8 Jul 2020 Philipp Roser, Xia Zhong, Annette Birkhold, Alexander Preuhs, Christopher Syben, Elisabeth Hoppe, Norbert Strobel, Markus Kowarschik, Rebecca Fahrig, Andreas Maier

Here, we propose a novel approach combining conventional techniques with learning-based methods to simultaneously estimate the forward-scatter reaching the detector as well as the back-scatter affecting the patient skin dose.

Blocking Multi-Task Learning

Appearance Learning for Image-based Motion Estimation in Tomography

no code implementations18 Jun 2020 Alexander Preuhs, Michael Manhart, Philipp Roser, Elisabeth Hoppe, Yixing Huang, Marios Psychogios, Markus Kowarschik, Andreas Maier

To this end, we train a siamese triplet network to predict the reprojection error (RPE) for the complete acquisition as well as an approximate distribution of the RPE along the single views from the reconstructed volume in a multi-task learning approach.

Motion Estimation Multi-Task Learning +1

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