4 citations · 8 across the 8 of their papers we have counts for
6 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…
PYRO-NN: Python Reconstruction Operators in Neural Networks
Christopher Syben, Markus Michen, Bernhard Stimpel +3
Purpose: Recently, several attempts were conducted to transfer deep learning to medical image reconstruction. An increasingly number of publications follow the concept of embedding…
A Gentle Introduction to Deep Learning in Medical Image Processing
Andreas Maier, Christopher Syben, Tobias Lasser +1
This paper tries to give a gentle introduction to deep learning in medical image processing, proceeding from theoretical foundations to applications. We first discuss general reaso…
User Loss -- A Forced-Choice-Inspired Approach to Train Neural Networks directly by User Interaction
Shahab Zarei, Bernhard Stimpel, Christopher Syben +1
In this paper, we investigate whether is it possible to train a neural network directly from user inputs. We consider this approach to be highly relevant for applications in which…
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…
Projection image-to-image translation in hybrid X-ray/MR imaging
Bernhard Stimpel, Christopher Syben, Tobias Würfl +5
The potential benefit of hybrid X-ray and MR imaging in the interventional environment is large due to the combination of fast imaging with high contrast variety. However, a vast a…