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Markus Hüllebrand

Showing results (1-10 of 12) with videos related to

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International Journal of Computer Assisted Radiology and Surgery|June 30, 2025
Carotid atherosclerotic lesion analysis in 3D based on distance encoding in mesh representationHinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter, et al.
Journal of Medical Imaging (Bellingham, Wash.)|July 15, 2024
Learning carotid vessel wall segmentation in black-blood MRI using sparsely sampled cross-sections from 3D dataHinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter, et al.
Physiological Measurement|February 3, 2023
Population-based reference values for 4D flow MRI derived aortic blood flow parametersMarie Schafstedde, Lina Jarmatz, Jan Brüning, et al.
Magnetic Resonance in Medicine|October 11, 2014
Spatiotemporal phase unwrapping for real-time phase-contrast flow MRIMarkus Untenberger, Markus Hüllebrand, Lennart Tautz, et al.
International Journal of Computer Assisted Radiology and Surgery|October 8, 2018
Virtual downsizing for decision support in mitral valve repairMathias Neugebauer, Lennart Tautz, Markus Hüllebrand, et al.
Circulation. Cardiovascular Imaging|June 18, 2024
Perfect Match: Radiomics and Artificial Intelligence in Cardiac ImagingBettina Baeßler, Sandy Engelhardt, Amar Hekalo, et al.
Scientific Reports|April 18, 2023
Characterization of aortic aging using 3D multi-parametric MRI-long-term follow-up in a population studySophie Loose, Demetris Solou, Christoph Strecker, et al.
International Journal of Computer Assisted Radiology and Surgery|August 4, 2018
Extraction of open-state mitral valve geometry from CT volumesLennart Tautz, Mathias Neugebauer, Markus Hüllebrand, et al.
International Journal of Computer Assisted Radiology and Surgery|January 23, 2022
Cascaded neural network-based CT image processing for aortic root analysisNina Krüger, Alexander Meyer, Lennart Tautz, et al.
Scientific Reports|March 11, 2026
Towards fully automated synthetic ECV quantification: an open-access machine learning-based approach for fast blood draw-free CMRRebecca Elisabeth Beyer, Markus Hüllebrand, Patrick Doeblin, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
International Journal of Computer Assisted Radiology and Surgery|June 30, 2025
Carotid atherosclerotic lesion analysis in 3D based on distance encoding in mesh representationHinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter, et al.
Journal of Medical Imaging (Bellingham, Wash.)|July 15, 2024
Learning carotid vessel wall segmentation in black-blood MRI using sparsely sampled cross-sections from 3D dataHinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter, et al.
Physiological Measurement|February 3, 2023
Population-based reference values for 4D flow MRI derived aortic blood flow parametersMarie Schafstedde, Lina Jarmatz, Jan Brüning, et al.
Magnetic Resonance in Medicine|October 11, 2014
Spatiotemporal phase unwrapping for real-time phase-contrast flow MRIMarkus Untenberger, Markus Hüllebrand, Lennart Tautz, et al.
International Journal of Computer Assisted Radiology and Surgery|October 8, 2018
Virtual downsizing for decision support in mitral valve repairMathias Neugebauer, Lennart Tautz, Markus Hüllebrand, et al.
Circulation. Cardiovascular Imaging|June 18, 2024
Perfect Match: Radiomics and Artificial Intelligence in Cardiac ImagingBettina Baeßler, Sandy Engelhardt, Amar Hekalo, et al.
Scientific Reports|April 18, 2023
Characterization of aortic aging using 3D multi-parametric MRI-long-term follow-up in a population studySophie Loose, Demetris Solou, Christoph Strecker, et al.
International Journal of Computer Assisted Radiology and Surgery|August 4, 2018
Extraction of open-state mitral valve geometry from CT volumesLennart Tautz, Mathias Neugebauer, Markus Hüllebrand, et al.
International Journal of Computer Assisted Radiology and Surgery|January 23, 2022
Cascaded neural network-based CT image processing for aortic root analysisNina Krüger, Alexander Meyer, Lennart Tautz, et al.
Scientific Reports|March 11, 2026
Towards fully automated synthetic ECV quantification: an open-access machine learning-based approach for fast blood draw-free CMRRebecca Elisabeth Beyer, Markus Hüllebrand, Patrick Doeblin, et al.
Pageof 2