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Respiratory Motion image navigator inav
Sequence and reconstruction framework of the proposed GB-BOOST sequence. Two interleaved electrocardiogram-triggered 3D volumes are acquired using 2-point Dixon GRE acquisition with IR and T2prep, respectively. <t>iNAV</t> enables 100% respiratory scan efficiency. A variable-density Cartesian trajectory with spiral-like profile order and golden-angle step is adopted with five-fold undersampling. Inline non-rigid MoCo iterative SENSE reconstruction and water/fat separation are performed to obtain IR and T2prep water/fat volumes, which is followed by offline HD-PROST denoising and PSIR reconstruction to finally produce IR GB-BOOST, T2prep GB-BOOST, and PSIR GB-BOOST images. GRE gradient echo, IR inversion recovery, T2prep T2 preparation, iNAV image navigator, MoCo motion corrected, <t>HD-PROST</t> <t>high-dimensional</t> patch-based low-rank regularization, PSIR phase sensitive inversion recovery, GB-BOOST Gray-Blood and Bright-blOOd phase SensiTive inversion recovery
Image Navigator Inav, supplied by Respiratory Motion, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/image+navigation+inav/pmc12811457-67-2-15?v=Respiratory+Motion
Average 86 stars, based on 1 article reviews
image navigator inav - by Bioz Stars, 2026-07
86/100 stars

Images

1) Product Images from "Comprehensive three-dimensional free-breathing magnetic resonance imaging for simultaneous myocardial viability and coronary artery visualization at 1.5T and 3T"

Article Title: Comprehensive three-dimensional free-breathing magnetic resonance imaging for simultaneous myocardial viability and coronary artery visualization at 1.5T and 3T

Journal: Journal of Cardiovascular Magnetic Resonance

doi: 10.1016/j.jocmr.2025.102672

Sequence and reconstruction framework of the proposed GB-BOOST sequence. Two interleaved electrocardiogram-triggered 3D volumes are acquired using 2-point Dixon GRE acquisition with IR and T2prep, respectively. iNAV enables 100% respiratory scan efficiency. A variable-density Cartesian trajectory with spiral-like profile order and golden-angle step is adopted with five-fold undersampling. Inline non-rigid MoCo iterative SENSE reconstruction and water/fat separation are performed to obtain IR and T2prep water/fat volumes, which is followed by offline HD-PROST denoising and PSIR reconstruction to finally produce IR GB-BOOST, T2prep GB-BOOST, and PSIR GB-BOOST images. GRE gradient echo, IR inversion recovery, T2prep T2 preparation, iNAV image navigator, MoCo motion corrected, HD-PROST high-dimensional patch-based low-rank regularization, PSIR phase sensitive inversion recovery, GB-BOOST Gray-Blood and Bright-blOOd phase SensiTive inversion recovery
Figure Legend Snippet: Sequence and reconstruction framework of the proposed GB-BOOST sequence. Two interleaved electrocardiogram-triggered 3D volumes are acquired using 2-point Dixon GRE acquisition with IR and T2prep, respectively. iNAV enables 100% respiratory scan efficiency. A variable-density Cartesian trajectory with spiral-like profile order and golden-angle step is adopted with five-fold undersampling. Inline non-rigid MoCo iterative SENSE reconstruction and water/fat separation are performed to obtain IR and T2prep water/fat volumes, which is followed by offline HD-PROST denoising and PSIR reconstruction to finally produce IR GB-BOOST, T2prep GB-BOOST, and PSIR GB-BOOST images. GRE gradient echo, IR inversion recovery, T2prep T2 preparation, iNAV image navigator, MoCo motion corrected, HD-PROST high-dimensional patch-based low-rank regularization, PSIR phase sensitive inversion recovery, GB-BOOST Gray-Blood and Bright-blOOd phase SensiTive inversion recovery

Techniques Used: Sequencing



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Sequence and reconstruction framework of the proposed GB-BOOST sequence. Two interleaved electrocardiogram-triggered 3D volumes are acquired using 2-point Dixon GRE acquisition with IR and T2prep, respectively. <t>iNAV</t> enables 100% respiratory scan efficiency. A variable-density Cartesian trajectory with spiral-like profile order and golden-angle step is adopted with five-fold undersampling. Inline non-rigid MoCo iterative SENSE reconstruction and water/fat separation are performed to obtain IR and T2prep water/fat volumes, which is followed by offline HD-PROST denoising and PSIR reconstruction to finally produce IR GB-BOOST, T2prep GB-BOOST, and PSIR GB-BOOST images. GRE gradient echo, IR inversion recovery, T2prep T2 preparation, iNAV image navigator, MoCo motion corrected, <t>HD-PROST</t> <t>high-dimensional</t> patch-based low-rank regularization, PSIR phase sensitive inversion recovery, GB-BOOST Gray-Blood and Bright-blOOd phase SensiTive inversion recovery
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Image Search Results


Sequence and reconstruction framework of the proposed GB-BOOST sequence. Two interleaved electrocardiogram-triggered 3D volumes are acquired using 2-point Dixon GRE acquisition with IR and T2prep, respectively. iNAV enables 100% respiratory scan efficiency. A variable-density Cartesian trajectory with spiral-like profile order and golden-angle step is adopted with five-fold undersampling. Inline non-rigid MoCo iterative SENSE reconstruction and water/fat separation are performed to obtain IR and T2prep water/fat volumes, which is followed by offline HD-PROST denoising and PSIR reconstruction to finally produce IR GB-BOOST, T2prep GB-BOOST, and PSIR GB-BOOST images. GRE gradient echo, IR inversion recovery, T2prep T2 preparation, iNAV image navigator, MoCo motion corrected, HD-PROST high-dimensional patch-based low-rank regularization, PSIR phase sensitive inversion recovery, GB-BOOST Gray-Blood and Bright-blOOd phase SensiTive inversion recovery

Journal: Journal of Cardiovascular Magnetic Resonance

Article Title: Comprehensive three-dimensional free-breathing magnetic resonance imaging for simultaneous myocardial viability and coronary artery visualization at 1.5T and 3T

doi: 10.1016/j.jocmr.2025.102672

Figure Lengend Snippet: Sequence and reconstruction framework of the proposed GB-BOOST sequence. Two interleaved electrocardiogram-triggered 3D volumes are acquired using 2-point Dixon GRE acquisition with IR and T2prep, respectively. iNAV enables 100% respiratory scan efficiency. A variable-density Cartesian trajectory with spiral-like profile order and golden-angle step is adopted with five-fold undersampling. Inline non-rigid MoCo iterative SENSE reconstruction and water/fat separation are performed to obtain IR and T2prep water/fat volumes, which is followed by offline HD-PROST denoising and PSIR reconstruction to finally produce IR GB-BOOST, T2prep GB-BOOST, and PSIR GB-BOOST images. GRE gradient echo, IR inversion recovery, T2prep T2 preparation, iNAV image navigator, MoCo motion corrected, HD-PROST high-dimensional patch-based low-rank regularization, PSIR phase sensitive inversion recovery, GB-BOOST Gray-Blood and Bright-blOOd phase SensiTive inversion recovery

Article Snippet: A two-dimensional image navigator (iNAV) is acquired before the acquisition of each volume to detect respiratory motion for motion-corrected reconstruction, enabling free-breathing acquisition with 100% respiratory scan efficiency .

Techniques: Sequencing

3D Dixon and 2D PSIR LGE imaging of patients with chronic myocardial infarction scanned at 3T. Respiratory ghosts were detected in the 2D PSIR LGE image, whereas the iNAV 3D Dixon LGE images demonstrated artifact-free visualization of LGE ( a and b ). 3D isotropic LGE imaging enables detection of diagnostically challenging subtle subendocardial lesions that remain elusive on conventional 2D sequence ( c and d ). 3D three-dimensional, 2D two-dimensional, PSIR phase-sensitive inversion recovery, LGE late gadolinium enhancement, iNAV image navigation

Journal: Journal of Cardiovascular Magnetic Resonance

Article Title: Free-breathing three-dimensional high-resolution Dixon late gadolinium enhancement imaging for chronic myocardial infarction assessment at 3T

doi: 10.1016/j.jocmr.2025.102668

Figure Lengend Snippet: 3D Dixon and 2D PSIR LGE imaging of patients with chronic myocardial infarction scanned at 3T. Respiratory ghosts were detected in the 2D PSIR LGE image, whereas the iNAV 3D Dixon LGE images demonstrated artifact-free visualization of LGE ( a and b ). 3D isotropic LGE imaging enables detection of diagnostically challenging subtle subendocardial lesions that remain elusive on conventional 2D sequence ( c and d ). 3D three-dimensional, 2D two-dimensional, PSIR phase-sensitive inversion recovery, LGE late gadolinium enhancement, iNAV image navigation

Article Snippet: Image navigation (iNAV) with direct respiratory motion tracking of the heart has been introduced and enables 100% respiratory gating efficiency and predictable scan time.

Techniques: Imaging, Sequencing

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.

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: Respiratory motion correction , Right hemidiaphragmatic navigator gating , Abdominal belt in combination with right hemidiaphragmatic navigator gating , 2D image navigator (iNav).

Techniques: Comparison, Diagnostic Assay, Software

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

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: Respiratory motion correction , Right hemidiaphragmatic navigator gating , Abdominal belt in combination with right hemidiaphragmatic navigator gating , 2D image navigator (iNav).

Techniques: Software

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.

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: Respiratory motion correction , Right hemidiaphragmatic navigator gating , Abdominal belt in combination with right hemidiaphragmatic navigator gating , 2D image navigator (iNav).

Techniques: