Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Jens Wetzl

Showing results (21-30 of 36) with videos related to

Pageof 4
Sort By:
The International Journal of Cardiovascular Imaging|January 4, 2026
Equivalence of feature-tracking-derived myocardial strain across spatial resolution and compressed sensing accelerationBaptiste O P Wyssa, Lindsey A Crowe, Jean-François Deux, et al.
Scientific Reports|February 6, 2023
Introduction of a cascaded segmentation pipeline for parametric T1 mapping in cardiovascular magnetic resonance to improve segmentation performanceDarian Viezzer, Thomas Hadler, Clemens Ammann, et al.
Magnetic Resonance in Medicine|March 20, 2026
Deep-Learning-Based Image Reconstruction to Improve End-Diastolic and Systolic Cardiac T1 MappingDaniel Amsel, Jens Wetzl, Daniel Giese, et al.
The International Journal of Cardiovascular Imaging|December 25, 2025
Assessing the robustness of an artificial intelligence segmentation model for quantitative cardiovascular magnetic resonance imaging across cardiac phenotypesHadil Saad, Clemens Ammann, Thomas Hadler, et al.
Computer Methods and Programs in Biomedicine|May 31, 2023
Lazy Luna: Extendible software for multilevel reader comparison in cardiovascular magnetic resonance imagingThomas Hadler, Clemens Ammann, Jens Wetzl, et al.
Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance|June 23, 2024
Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translationQiang Zhang, Anastasia Fotaki, Sona Ghadimi, et al.
Journal of Magnetic Resonance Imaging : JMRI|October 4, 2025
Quantitative Confounder Analysis of Electrocardiogram Signals in Cardiac Magnetic Resonance at 1.5, 3 and 7 T-Assessing Standardized Electrode Positions and Sequence Types-Towards Quality AssuranceRichard Hickstein, Stephanie Wiesemann, Darian Viezzer, et al.
European Radiology|March 17, 2022
Low-dose contrast-enhanced time-resolved angiography with stochastic trajectories with iterative reconstruction (IT-TWIST-MRA) in brain arteriovenous shuntAkihiko Sakata, Ryo Sakamoto, Yasutaka Fushimi, et al.
Scientific Reports|April 23, 2022
Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imagingThomas Hadler, Jens Wetzl, Steffen Lange, et al.
European Radiology|January 19, 2020
Quantitative mechanical dyssynchrony in dilated cardiomyopathy measured by deformable registration algorithmYuanwei Xu, Shuai He, Weihao Li, et al.
Pageof 4

Showing results (21-30 of 36) with videos related to

Sort By:
Pageof 4
The International Journal of Cardiovascular Imaging|January 4, 2026
Equivalence of feature-tracking-derived myocardial strain across spatial resolution and compressed sensing accelerationBaptiste O P Wyssa, Lindsey A Crowe, Jean-François Deux, et al.
Scientific Reports|February 6, 2023
Introduction of a cascaded segmentation pipeline for parametric T1 mapping in cardiovascular magnetic resonance to improve segmentation performanceDarian Viezzer, Thomas Hadler, Clemens Ammann, et al.
Magnetic Resonance in Medicine|March 20, 2026
Deep-Learning-Based Image Reconstruction to Improve End-Diastolic and Systolic Cardiac T1 MappingDaniel Amsel, Jens Wetzl, Daniel Giese, et al.
The International Journal of Cardiovascular Imaging|December 25, 2025
Assessing the robustness of an artificial intelligence segmentation model for quantitative cardiovascular magnetic resonance imaging across cardiac phenotypesHadil Saad, Clemens Ammann, Thomas Hadler, et al.
Computer Methods and Programs in Biomedicine|May 31, 2023
Lazy Luna: Extendible software for multilevel reader comparison in cardiovascular magnetic resonance imagingThomas Hadler, Clemens Ammann, Jens Wetzl, et al.
Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance|June 23, 2024
Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translationQiang Zhang, Anastasia Fotaki, Sona Ghadimi, et al.
Journal of Magnetic Resonance Imaging : JMRI|October 4, 2025
Quantitative Confounder Analysis of Electrocardiogram Signals in Cardiac Magnetic Resonance at 1.5, 3 and 7 T-Assessing Standardized Electrode Positions and Sequence Types-Towards Quality AssuranceRichard Hickstein, Stephanie Wiesemann, Darian Viezzer, et al.
European Radiology|March 17, 2022
Low-dose contrast-enhanced time-resolved angiography with stochastic trajectories with iterative reconstruction (IT-TWIST-MRA) in brain arteriovenous shuntAkihiko Sakata, Ryo Sakamoto, Yasutaka Fushimi, et al.
Scientific Reports|April 23, 2022
Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imagingThomas Hadler, Jens Wetzl, Steffen Lange, et al.
European Radiology|January 19, 2020
Quantitative mechanical dyssynchrony in dilated cardiomyopathy measured by deformable registration algorithmYuanwei Xu, Shuai He, Weihao Li, et al.
Pageof 4