Search Results for author: Elisabeth Hoppe

Found 6 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

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

RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting

no code implementations9 Jul 2019 Elisabeth Hoppe, Florian Thamm, Gregor Körzdörfer, Christopher Syben, Franziska Schirrmacher, Mathias Nittka, Josef Pfeuffer, Heiko Meyer, Andreas Maier

Although the acquisition is highly accelerated, the state-of-the-art reconstruction suffers from long computation times: Template matching methods are used to find the most similar signal to the measured one by comparing it to pre-simulated signals of possible parameter combinations in a discretized dictionary.

Magnetic Resonance Fingerprinting Template Matching

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