343 citations
- Philips (Netherlands)NL6 papers
- Technical University of MunichDE5 papers
- KTH Royal Institute of TechnologySE4 papers
- RWTH Aachen UniversityDE4 papers
- TUM KlinikumDE4 papers
- Hamburg University of TechnologyDE3 papers
- Philips (Sweden)SE3 papers
- University Medical Center Hamburg-EppendorfDE3 papers
- University of LübeckDE3 papers
- Eindhoven University of TechnologyNL2 papers
- Fraunhofer Institute for Digital MedicineDE2 papers
- Harvard UniversityUS2 papers
36 papers
Depth to Anatomy: Organ Localization from Depth Images for Automated Patient Table Positioning in Radiology Workflow
Eytan Kats, Kai Geissler, Daniel Mensing +4
In clinical radiology, accurate patient table positioning is essential to align specific internal organs of interest with the scanner imaging isocenter, ensuring image quality and…
Technical Note: Low-Dose Simulation for Grating-Based X-Ray Dark-Field Radiography Using a Virtually Decreased Irradiation Area
Henriette Bast, Rafael C. Schick, Thomas Koehler +1
Background: X-ray dark-field radiography uses small-angle scattering to visualize the structural integrity of lung alveoli. To study the influence of dose reduction on clinical dar…
Beam Hardening Correction in Clinical X-ray Dark-Field Chest Radiography using Deep Learning-Based Bone Segmentation
Lennard Kaster, Maximilian E. Lochschmidt, Anne M. Bauer +5
Dark-field radiography is a novel X-ray imaging modality that enables complementary diagnostic information by visualizing the microstructural properties of lung tissue. Implemented…
Look-Up Table-Correction for Beam Hardening-Induced Signal of Clinical Dark-Field Chest Radiographs
Maximilian E. Lochschmidt, Theresa Urban, Lennard Kaster +4
Background: Material structures at the micrometer scale cause ultra-small-angle X-ray scattering, e.g., seen in lung tissue or plastic foams. In grating-based X-ray imaging, this c…
Motion-Robust T2* Quantification from Gradient Echo MRI with Physics-Informed Deep Learning
Hannah Eichhorn, Veronika Spieker, Kerstin Hammernik +5
Purpose: T2* quantification from gradient echo magnetic resonance imaging is particularly affected by subject motion due to the high sensitivity to magnetic field inhomogeneities,…
Relaxometry and contrast-free cerebral microvascular quantification using balanced Steady-State Free Precession MR Fingerprinting
Thomas Coudert, Aurélien Delphin, Antoine Barrier +7
This study proposes a novel, contrast-free Magnetic Resonance Fingerprinting (MRF) method using balanced Steady-State Free Precession (bSSFP) sequences for the quantification of ce…