Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
369-04-002 ISMRM Abstract

Denoising High Resolution Intracranial Vessel Wall Imaging at 7T

Primary: Analysis Methods - Image Enhancement
Secondary: Cardiovascular - Vascular and Vessel Wall
369-04-002 · Visualizing Intracranial and Carotid Arteries: MRA, VWI, and Beyond · Monday, 11 May, 2:45 PM–3:40 PM · Digital Posters Row J
Keywords: Vessel Wall Neurovascular High-resolution vessel wall imaging Denoising Intracranial vessel wall imaging
Accepted
Tudor V Sava 1,2, Rebecca Glarin1,2, Bahman Tahayori1,2, Warda Syeda1,2, Yasmin Blunck1,3, Bradford A Moffat1,2, Leigh Johnston1,2,3
1Melbourne Brain Centre Imaging Unit, University of Melbourne, Melbourne, Australia
2Department of Radiology, University of Melbourne, Melbourne, Australia
3Department of Biomedical Engineering and Graeme Clark Institute, University of Melbourne, Melbourne, Australia
Presenting Author: Tudor V Sava

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Lindenholz A, van der Kolk AG, Zwanenburg JJM, Hendrikse J. The Use and Pitfalls of Intracranial Vessel Wall Imaging: How We Do It. Radiology. 2018 Jan;286(1):12–28. doi:10.1148/radiol.2017162096 [doi]
2. Gutierrez J, Elkind MSV, Petito C, Chung DY, Dwork AJ, Marshall RS. The contribution of HIV infection to intracranial arterial remodeling: A pilot study. Neuropathology. 2013;33(3):256–63. doi:10.1111/j.1440-1789.2012.01358.x [doi]
3. Tyshchenko I, Zeng Y, Blunck Y, Moffat B, Glarin R, Johnston L. Modular open-source imaging phantom. Proc. Intl. Soc. Mag. Reson. Med. 2024;32:1321 doi:10.58530/2024/1321 [doi]
4. Maggioni M, Katkovnik V, Egiazarian K, Foi A. Nonlocal transform-domain filter for volumetric data denoising and reconstruction. IEEE Trans Image Process. 2013;22(1):119–133. doi:10.1109/TIP.2012.2210725 [doi]
5. Tustison NJ, Avants BB, Cook PA, et al. Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements. NeuroImage. 2014;99:166–179. doi:10.1016/j.neuroimage.2014.05.044 [doi]
6. Esteban O, Birman D, Schaer M, Koyejo OO, Poldrack RA, Gorgolewski KJ. MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites. PLoS One. 2017;12(9):e0184661. doi:10.1371/journal.pone.0184661 [doi]
7. Ganzetti M, Wenderoth N, Mantini D. Intensity inhomogeneity correction of structural MR images: A data-driven approach to define input algorithm parameters. Front Neuroinform. 2016;10:10. doi:10.3389/fninf.2016.00010 [doi]
8. Forman SD, Cohen JD, Fitzgerald M, Eddy WF, Mintun MA, Noll DC. Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): Use of a cluster-size threshold. Magn Reson Med. 1995;33(5):636–647. doi:10.1002/mrm.1910330508 [doi]
9. Bazin P-L, Alkemade A, van der Zwaag W, Caan M, Mulder M, Forstmann BU. Denoising high-field multi-dimensional MRI with local complex PCA. Front Neurosci. 2019;13:1066. doi:10.3389/fnins.2019.01066 [doi]
10. National Electrical Manufacturers Association (NEMA). Determination of Signal-to-Noise Ratio (SNR) in Diagnostic Magnetic Resonance Imaging. 2015 Apr 30. Accessed 2024 Nov 7. Available from: https://www.nema.org/Standards/view/Determination-of-Signal-to-Noise-Ratio-in-Diagnostic-Magnetic-Resonance-Imaging
11. Sijbers J, Scheunders P, Bonnet N, Van Dyck D, Raman E. Quantification and improvement of the signal-to-noise ratio in a magnetic resonance image acquisition procedure. Magn Reson Imaging. 1996;14(10):1157–1163. doi:10.1016/S0730-725X(96)00219-6 [doi]
12. Dou Q, Wang Z, Feng X, Campbell‐Washburn AE, Mugler JP, Meyer CH. MRI denoising with a non‐blind deep complex‐valued convolutional neural network. NMR Biomed. 2025 Jan;38(1):e5291. doi:10.1002/nbm.5291 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/369-04-002