Tobias Würfl | DeepAI

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Featured Co-authors

Yoshua Bengio
434 publications
Daniel Rueckert
177 publications
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111 publications
Andreas Maier
84 publications
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39 publications
Nishant Ravikumar
34 publications
Aggelos K. Katsaggelos
33 publications
Oliver Cossairt
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Vincent Christlein
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∙ 12/08/2020

2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network

Computed tomography is widely used to examine internal structures in a n...

0 Haoyu Wei, et al. ∙

∙ 11/12/2020

Disassemblable Fieldwork CT Scanner Using a 3D-printed Calibration Phantom

The use of computed tomography (CT) imaging has become of increasing int...

0 Florian Schiffers, et al. ∙

∙ 11/19/2019

Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging

Hybrid X-ray and magnetic resonance (MR) imaging promises large potentia...

21 Bernhard Stimpel, et al. ∙

∙ 10/18/2019

The TCGA Meta-Dataset Clinical Benchmark

Machine learning is bringing a paradigm shift to healthcare by changing ...

9 Mandana Samiei, et al. ∙

∙ 09/14/2019

Torchmeta: A Meta-Learning library for PyTorch

The constant introduction of standardized benchmarks in the literature h...

20 Tristan Deleu, et al. ∙

∙ 07/03/2019

Learning with Known Operators reduces Maximum Training Error Bounds

We describe an approach for incorporating prior knowledge into machine l...

3 Andreas K. Maier, et al. ∙

∙ 07/09/2018

Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion

In this paper, we derive a neural network architecture based on an analy...

14 Christopher Syben, et al. ∙

∙ 06/28/2018

Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction

Deep learning approaches have shown promising performance for compressed...

4 Maximilian Seitzer, et al. ∙

∙ 04/11/2018

Projection image-to-image translation in hybrid X-ray/MR imaging

The potential benefit of hybrid X-ray and MR imaging in the intervention...

0 Bernhard Stimpel, et al. ∙

∙ 01/12/2018

Deep Learning for Sampling from Arbitrary Probability Distributions

This paper proposes a fully connected neural network model to map sample...

0 Felix Horger, et al. ∙

∙ 12/01/2017

Precision Learning: Towards Use of Known Operators in Neural Networks

In this paper, we consider the use of prior knowledge within neural netw...

0 Andreas Maier, et al. ∙

∙ 11/09/2017

Frangi-Net: A Neural Network Approach to Vessel Segmentation

In this paper, we reformulate the conventional 2-D Frangi vesselness mea...

0 Weilin Fu, et al. ∙

∙ 10/20/2017

MR to X-Ray Projection Image Synthesis

Hybrid imaging promises large potential in medical imaging applications....

0 Bernhard Stimpel, et al. ∙

∙ 10/17/2017

A Deep Learning Approach for Reconstruction Filter Kernel Discretization

In this paper, we present substantial evidence that a deep neural networ...

0 Christopher Syben, et al. ∙