147 citations · 234 across the 13 of their papers we have counts for
7 papers · 1 filter
Reconstruction of Voxels with Position- and Angle-Dependent Weightings
Lina Felsner, Tobias Würfl, Christopher Syben +4
The reconstruction problem of voxels with individual weightings can be modeled a position- and angle- dependent function in the forward-projection. This changes the system matrix a…
Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion
Christopher Syben, Bernhard Stimpel, Jonathan Lommen +3
In this paper, we derive a neural network architecture based on an analytical formulation of the parallel-to-fan beam conversion problem following the concept of precision learning…
Precision Learning: Towards Use of Known Operators in Neural Networks
Andreas Maier, Frank Schebesch, Christopher Syben +4
In this paper, we consider the use of prior knowledge within neural networks. In particular, we investigate the effect of a known transform within the mapping from input data space…
Frangi-Net: A Neural Network Approach to Vessel Segmentation
Weilin Fu, Katharina Breininger, Tobias Würfl +3
In this paper, we reformulate the conventional 2-D Frangi vesselness measure into a pre-weighted neural network ("Frangi-Net"), and illustrate that the Frangi-Net is equivalent to…
MR to X-Ray Projection Image Synthesis
Bernhard Stimpel, Christopher Syben, Tobias Würfl +3
Hybrid imaging promises large potential in medical imaging applications. To fully utilize the possibilities of corresponding information from different modalities, the information…
Precision Learning: Reconstruction Filter Kernel Discretization
Christopher Syben, Bernhard Stimpel, Katharina Breininger +4
In this paper, we present substantial evidence that a deep neural network will intrinsically learn the appropriate way to discretize the ideal continuous reconstruction filter. Cur…
Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images -- A Cross-Site Robustness Assessment
Marc Aubreville, Miguel Goncalves, Christian Knipfer +6
Deep learning technologies such as convolutional neural networks (CNN) provide powerful methods for image recognition and have recently been employed in the field of automated carc…