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06/01/2022
A comparative study between vision transformers and CNNs in digital pathology
Recently, vision transformers were shown to be capable of outperforming ...
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11/29/2019
Deep autofocus with cone-beam CT consistency constraint
High quality reconstruction with interventional C-arm cone-beam computed...
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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...
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11/18/2019
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
Deep learning-based image processing is capable of creating highly appea...
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10/09/2019
Image Quality Assessment for Rigid Motion Compensation
Diagnostic stroke imaging with C-arm cone-beam computed tomography (CBCT...
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07/03/2019
Learning with Known Operators reduces Maximum Training Error Bounds
We describe an approach for incorporating prior knowledge into machine l...
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04/30/2019
PYRO-NN: Python Reconstruction Operators in Neural Networks
Purpose: Recently, several attempts were conducted to transfer deep lear...
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07/24/2018
User Loss -- A Forced-Choice-Inspired Approach to Train Neural Networks directly by User Interaction
In this paper, we investigate whether is it possible to train a neural n...
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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...
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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...
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10/20/2017
MR to X-Ray Projection Image Synthesis
Hybrid imaging promises large potential in medical imaging applications....
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10/17/2017
