360-01-015 Registered Abstract

Validation of A Data-Consistent Retrospective Respiratory Motion Correction Method in Multi-Channel Human MRI Data

Primary: Acquisition & Reconstruction - Motion Correction: Non-Neuro

Secondary: Acquisition & Reconstruction - Image Reconstruction: Non-AI

360-01-015 · MOCO from Head to Toe · Monday, 11 May, 8:20 AM–9:15 AM · Digital Posters Row A

Keywords: Image Reconstruction Respiratory motion correction Retrospective Motion Correction Golden-angle radial sampling Data consistency

Accepted

Liliana B Edmonds ¹, Michael Fieseler², Christian Licht¹, George Soultanidis³, Georg Schramm⁴, Klaus P Schafers², Zahi A Fayad³, Philip M Robson³, Fernando E Boada¹

¹Department of Radiology, Stanford University, Stanford, United States of America

²European Institute for Molecular Imaging, University of Muenster, Muenster, Germany

³BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, United States of America

⁴Nuclear Medicine, KU Leuven, Leuven, Belgium

Presenting Author: Liliana B Edmonds

Synopsis

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References

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3. Rigie, D., et al. "Cardiorespiratory motion-tracking via self-refocused rosette navigators." Magn Reson Med 81.5 (2019): 2947–2958. DOI: 10.1002/mrm.27609. [doi]

4. Fieseler, M., et al. "Data-consistent retrospective motion correction and co-registration." ISMRM Abstract.

5. Vercauteren, T. et al. “Diffeomorphic demons: Efficient non-parametric image registration.” NeuroImage 45.1 (2009): S61-S72.

6. Uecker M, et al. ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med. 71.3 (2014) : 990-1001. DOI: 10.1002/mrm.24751. [doi]

7. Zhu X, et al. Iterative motion-compensation reconstruction ultra-short TE (iMoCo UTE) for high-resolution free-breathing pulmonary MRI. Magn Reson Med. 83 (2020): 1208–1221. DOI: 10.1002/mrm.27998. [doi]

8. Segars WP, et al. "4D XCAT phantom for multimodality imaging research." Medical physics 37.9 (2010): 4902-4915. DOI: 10.1118/1.3480985 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/360-01-015