Search Results for author: Michael Manhart

Found 6 papers, 1 papers with code

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

Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images

no code implementations20 May 2020 Yixing Huang, Alexander Preuhs, Michael Manhart, Guenter Lauritsch, Andreas Maier

For example, for truncated data, DCR achieves a mean root-mean-square error of 24 HU and a mean structure similarity index of 0. 999 inside the field-of-view for different patients in the noisy case, while the state-of-the-art U-Net method achieves 55 HU and 0. 995 respectively for these two metrics.

Computed Tomography (CT) Image Reconstruction

Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior

no code implementations19 Aug 2019 Yixing Huang, Alexander Preuhs, Guenter Lauritsch, Michael Manhart, Xiaolin Huang, Andreas Maier

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 unseen data; b) deep learning methods are sensitive to noise.

Cannot find the paper you are looking for? You can Submit a new open access paper.