40 citations · 44 across the 9 of their papers we have counts for
9 papers
From Lines to Shapes: Geometric-Constrained Segmentation of X-Ray Collimators via Hough Transform
Benjamin El-Zein, Dominik Eckert, Andreas Fieselmann +4
Collimation in X-ray imaging restricts exposure to the region-of-interest (ROI) and minimizes the radiation dose applied to the patient. The detection of collimator shadows is an e…
A Realistic Collimated X-Ray Image Simulation Pipeline
Benjamin El-Zein, Dominik Eckert, Thomas Weber +4
Collimator detection remains a challenging task in X-ray systems with unreliable or non-available information about the detectors position relative to the source. This paper presen…
An Interpretable X-ray Style Transfer via Trainable Local Laplacian Filter
Dominik Eckert, Ludwig Ritschl, Christopher Syben +5
Radiologists have preferred visual impressions or 'styles' of X-ray images that are manually adjusted to their needs to support their diagnostic performance. In this work, we propo…
StyleX: A Trainable Metric for X-ray Style Distances
Dominik Eckert, Christopher Syben, Christian Hümmer +3
The progression of X-ray technology introduces diverse image styles that need to be adapted to the preferences of radiologists. To support this task, we introduce a novel deep lear…
Metal-conscious Embedding for CBCT Projection Inpainting
Fuxin Fan, Yangkong Wang, Ludwig Ritschl +6
The existence of metallic implants in projection images for cone-beam computed tomography (CBCT) introduces undesired artifacts which degrade the quality of reconstructed images. I…
Simulation-Driven Training of Vision Transformers Enabling Metal Segmentation in X-Ray Images
Fuxin Fan, Ludwig Ritschl, Marcel Beister +5
In several image acquisition and processing steps of X-ray radiography, knowledge of the existence of metal implants and their exact position is highly beneficial (e.g. dose regula…
Deep Learning-based Denoising of Mammographic Images using Physics-driven Data Augmentation
Dominik Eckert, Sulaiman Vesal, Ludwig Ritschl +2
Mammography is using low-energy X-rays to screen the human breast and is utilized by radiologists to detect breast cancer. Typically radiologists require a mammogram with impeccabl…
Learning to recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks
Sebastian Guendel, Sasa Grbic, Bogdan Georgescu +4
Chest X-ray is the most common medical imaging exam used to assess multiple pathologies. Automated algorithms and tools have the potential to support the reading workflow, improve…
The rotate-plus-shift C-arm trajectory: Complete CT data with less than 180° rotation
Ludwig Ritschl, Jan Kuntz, Marc Kachelrieß
In the last decade C-arm-based cone-beam CT became a widely used modality for intraoperative imaging. Typically a C-arm scan is performed using a circle-like trajectory around a re…