research
∙
12/03/2019
Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-beam CT
Analyzing knee cartilage thickness and strain under load can help to fur...
share
research
∙
11/29/2019
Deep autofocus with cone-beam CT consistency constraint
High quality reconstruction with interventional C-arm cone-beam computed...
research
∙
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...
research
∙
11/18/2019
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
Deep learning-based image processing is capable of creating highly appea...
research
∙
10/09/2019
Image Quality Assessment for Rigid Motion Compensation
Diagnostic stroke imaging with C-arm cone-beam computed tomography (CBCT...
research
∙
09/13/2019
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquirin...
research
∙
07/09/2019
RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
Recently, Magnetic Resonance Fingerprinting (MRF) was proposed as a quan...
research
∙
07/03/2019
Learning with Known Operators reduces Maximum Training Error Bounds
We describe an approach for incorporating prior knowledge into machine l...
research
∙
04/30/2019
PYRO-NN: Python Reconstruction Operators in Neural Networks
Purpose: Recently, several attempts were conducted to transfer deep lear...
research
∙
10/12/2018
A Gentle Introduction to Deep Learning in Medical Image Processing
This paper tries to give a gentle introduction to deep learning in medic...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
10/20/2017
MR to X-Ray Projection Image Synthesis
Hybrid imaging promises large potential in medical imaging applications....
research
∙
10/17/2017
