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Respiratory Motion
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Journal: Journal of Cardiovascular Magnetic Resonance
Article Title: Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis
doi: 10.1016/j.jocmr.2024.101097
Figure Lengend Snippet: Summary of the iNav-AUTO CMRA study protocol in comparison to the two previous non–contrast-enhanced multi-center studies assessing the diagnostic accuracy of CMRA.
Article Snippet:
Techniques: Comparison, Diagnostic Assay, Software
Journal: Journal of Cardiovascular Magnetic Resonance
Article Title: Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis
doi: 10.1016/j.jocmr.2024.101097
Figure Lengend Snippet: Appearance of the iNav-AUTO CMRA acquisition planning. The image slab including oversampling (yellow) and 2D image navigator (iNav) (blue) are automatically determined by a deep-learning–based tool which is part of work-in-progress software (Siemens Healthineers, cardiac dot companion). iNav-AUTO CMRA image navigator–based, automated coronary magnetic resonance angiography, 2D two-dimensional
Article Snippet:
Techniques: Software
Journal: Journal of Cardiovascular Magnetic Resonance
Article Title: Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis
doi: 10.1016/j.jocmr.2024.101097
Figure Lengend Snippet: Illustration of the protocol for whole-heart free-breathing sub-millimeter iNav-AUTO CMRA acquisition. (A) Acquisition of undersampled CMRA images. 2D image navigators (iNav) to mitigate respiratory-induced motion and to allow 100% respiratory scan efficiency precedes acquisition with 3D variable density, spiral-like Cartesian trajectory with golden angle between spiral-like interleaves (VD-CASPR). (B) Motion correction. Before reconstruction, the inferior-superior and left-right respiratory motion is estimated from the 2D iNavs. The data are then allocated into respiratory bins. Soft-gated iterative SENSE is used to reconstruct each respiratory bin. Non–rigid 3D motion is then estimated from these respiratory bin datasets via image registration. (C) Image reconstruction. 3D non–rigid motion-corrected iterative SENSE undersampled reconstruction with patch–based low-rank denoising (PROST) is then used to generate the final CMRA image. iNav-AUTO CMRA image navigator–based, automated coronary magnetic resonance angiography, 2D two-dimensional, 3D three-dimensional, SENSE sensitivity encoding, ECG electrocardiogram, FATSAT; fat saturation.
Article Snippet:
Techniques: