Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
630-01-009 ISMRM Abstract

Dipole-lets (𝔇): a new multiscale framework for MR phase/QSM analysis and reconstruction

Primary: Contrast Mechanisms - Susceptibility/QSM
Secondary: Contrast Mechanisms - Electromagnetic Tissue Properties
630-01-009 · Quantitative Susceptibility Mapping: From Phase to Tissue Properties · Thursday, 14 May, 8:30 AM–10:20 AM · Meeting Room 2.60
Keywords: Quantitative Susceptibility Mapping (QSM) Inverse Problem Multiscale transforms
Accepted
Carlos Milovic1,2, Ignacio Contreras-Zúñiga 2, Mathias Lambert3,4, Cristian Tejos1,2,5
1Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
2Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile
3Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, Chile
4Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, Chile
5Millennium Institute Millennium Institute for Intelligent Healthcare Engineering (iHEALTH), Pontificia Universidad Católica de Chile, Santiago, Chile
Presenting Author: Ignacio Contreras-Zúñiga

Synopsis

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References

1. [1] Bilgic B, Costagli M, Chan KS, et al. Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. Magn Reson Med. 2024;91(5):1834–1862. doi:10.1002/mrm.30006. [doi]
2. [2] Wu B, Li W, Guidon A, Liu C. Whole brain susceptibility mapping using compressed sensing. Magn Reson Med. 2012;67(1):137–147. doi:10.1002/mrm.23000. [doi]
3. [3] Fuchs P, Shmueli K. Incomplete spectrum QSM using support information. Front Neurosci. 2023;17:1130524. doi:10.3389/fnins.2023.1130524. [doi]
4. [4] Ahn HS, Park SH, Ye JC. Quantitative susceptibility map reconstruction using annihilating filter‐based low‐rank Hankel matrix approach. Magn Reson Med. 2020;83(3):858–871. doi:10.1002/mrm.27976. [doi]
5. [5] Huang S, Lah JJ, Allen JW, Qiu D. Robust quantitative susceptibility mapping via approximate message passing with parameter estimation. Magn Reson Med. 2023;90(4):1414–1430. doi:10.1002/mrm.29722. [doi]
6. [6] Starck JL, Murtagh F, Fadili JM. Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity. 2nd ed. Cambridge, UK: Cambridge University Press; 2015.
7. [7] Stiegeler J, Straub S. Shearlet-based susceptibility map reconstruction with iterative reweighting and nonlinear data fitting. Proc Intl Soc Magn Reson Med. 2020;28:3246. Available at: archive.ismrm.org/2020/3246.
8. [8] Langkammer C, Schweser F, Shmueli K, et al. Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge. Magn Reson Med. 2018;79(3):1661–1673. doi:10.1002/mrm.26830. [doi]
9. [9] Liu C. Susceptibility tensor imaging. Magn Reson Med. 2010;63(6):1471–1477. doi:10.1002/mrm.22482. [doi]
10. [10] Milovic C, Bilgic B, Zhao B, Acosta-Cabronero J, Tejos C. Fast nonlinear susceptibility inversion with variational regularization. Magn Reson Med. 2018;80(2):814–821. doi:10.1002/mrm.27073. [doi]
11. [11] QSM Challenge 2.0 Organization Committee; Bilgic B, Langkammer C, Marques JP, Meineke J, Milovic C, Schweser F. QSM reconstruction challenge 2.0: Design and report of results. Magn Reson Med. 2021;86(3):1241–1255. doi:10.1002/mrm.28754. [doi]
12. [12] Milovic C, Tejos C, Silva J, Shmueli K, Irarrazaval P. XSIM: A structural similarity index measure optimized for MRI QSM. Magn Reson Med. 2025;93(1):411–421. doi:10.1002/mrm.30271. [doi]
13. [13] Polak D, Chatnuntawech I, Yoon J, Iyer SS, Milovic C, Lee J, Bachert P, Adalsteinsson E, Setsompop K, Bilgic B. Nonlinear dipole inversion (NDI) enables robust quantitative susceptibility mapping (QSM). NMR Biomed. 2020;33(12):e4271. doi:10.1002/nbm.4271. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/630-01-009