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Abstract #3971

Robust Masking Techniques for Multi-Echo Quantitative Susceptibility Mapping

Ashley Stewart1,2, Simon Daniel Robinson2,3, Kieran O'Brien1,2,4, Jin Jin1,2,4, Georg Widhalm5, Gilbert Hangel3,5, Angela Walls6, Jonathan Goodwin7,8, Korbinian Eckstein3, Markus Barth1,2,9, and Steffen Bollmann1,2,9
1Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia, 2Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 3High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria, 4Siemens Healthcare Pty Ltd, Brisbane, Australia, 5Department of Neurosurgery, Medical University of Vienna, Vienna, Austria, 6Clinical & Research Imaging Centre, South Australian Health and Medical Research Institute, Adelaide, Australia, 7Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, Australia, 8School of Mathematical and Physical Science, University of Newcastle, Newcastle, Australia, 9School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia

Quantitative Susceptibility Mapping (QSM) is a post-processing technique applied to gradient-echo phase data. QSM generally requires a signal mask to identify reliable phase values before reconstruction. Most QSM pipelines do not include masking procedures, and often suggest masking techniques that introduce artefacts, work only in the human brain, and lose critical information, especially near strong susceptibility sources. We propose two novel echo-dependent masking strategies and find that they significantly reduce streaking artefacts, particularly surrounding strong sources and tissue boundaries in multi-echo data. Our techniques are open-source and implemented in a new framework for automated, scalable, and robust QSM processing.

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