Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
401-03-010 ISMRM Abstract

MR RawDeface: An Open Source, Automated Tool for Removal of Identifying Facial Features from Raw Multi-Channel k-Space Data

Primary: Acquisition & Reconstruction - Open source software, sequences, and reconstruction algorithms
Secondary: Analysis Methods - Software Tools
401-03-010 · End-to-End Software Innovation · Tuesday, 12 May, 1:40 PM–3:30 PM · Hall 1A
Keywords: Data Processing Software Tools Open-source software De-identification De-facing
Accepted
Selina Liu1, Mark Chiew 2,3
1Engineering Science, University of Toronto, Toronto, Canada
2Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
3Department of Medical Biophysics, University of Toronto, Toronto, Canada
Presenting Author: Mark Chiew

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References

1. C. G. Schwarz et al., “Identification of Anonymous MRI Research Participants with Face-Recognition Software,” New England Journal of Medicine, vol. 381, no. 17, pp. 1684–1686, Oct. 2019, doi: https://doi.org/10.1056/nejmc1908881. [doi]
2. C. Gao, B. A. Landman, J. L. Prince, and A. Carass, “A reproducibility evaluation of the effects of MRI defacing on brain segmentation,” medRxiv (Cold Spring Harbor Laboratory), May 2023, doi: https://doi.org/10.1101/2023.05.15.23289995. [doi]
3. M Rempe et al., “K-Strip: A Novel Segmentation Algorithm in k-Space for the Application of Skull Stripping.” Computer Methods and Programs in Biomedicine 243 (January 2024): 107912. doi: https://doi.org/10.1016/j.cmpb.2023.107912. [doi]
4. H Mattern, M Knoll, F Lüsebrink, and O Speck "Chemical sHift bAsed pRospectIve k-Space anonyMizAtion (CHARISMA)", ISMRM 2020 #1049
5. D. Kim et al., “Region-optimized virtual (ROVir) coils: Localization and/or suppression of spatial regions using sensor-domain beamforming,” Feb. 2021, doi: https://doi.org/10.1002/mrm.28706. [doi]
6. J. Wasserthal et al., “TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images,” Jul. 2023, doi: https://doi.org/10.1148/ryai.230024. [doi]
7. R. Souza et al., “An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement,” NeuroImage, vol. 170, pp. 482–494, Apr. 2018, doi: https://doi.org/10.1016/j.neuroimage.2017.08.021. [doi]
8. A. Fedorov et al., “3D Slicer as an Image Computing Platform for the Quantitative Imaging Network,” Magnetic Resonance Imaging, vol. 30, no. 9, pp. 1323–1341, Nov. 2012, doi: 10.1016/j.mri.2012.05.001. [doi]

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http://echo.ismrm.org/p/ISMRM2026/401-03-010