Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
566-05-002 ISMRM Abstract

Deep Learning Accelerated Slice Encoding for Metal Artifact Correction (SEMAC) for Hip Arthroplasty MRI

Primary: Musculoskeletal - Whole Joint
Secondary: Acquisition & Reconstruction - Subsampling: Parallel imaging, compressed sensing and low-rank modeling
566-05-002 · MSK: Clinical and Cutting-Edge · Wednesday, 13 May, 4:00 PM–4:55 PM · Digital Posters Row G
Keywords: Hips Metal SEMAC Deep-learning-based image reconstruction Acceleration
Accepted
Jeanette C Deck 1,2,3, Thomas Yu3,4,5, Andreas Walch1,2, Dominik Paul6, Mathias Nittka6, Marcel Dominik Nickel6, Reto Sutter1,2, Constantin von Deuster3,7
1Faculty of Medicine, University of Zurich, Zurich, Switzerland
2Department of Radiology, Balgrist University Hospital, Zurich, Switzerland
3Swiss Innovation Hub (SIH), Siemens Healthineers International AG, Lausanne, Switzerland
4LTS5, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
5Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
6Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
7Swiss Center for Musculoskeletal Imaging (SCMI), Balgrist Campus AG, Zurich, Switzerland
Presenting Author: Jeanette C Deck

Synopsis

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References

1. Lu W, Pauly KB, Gold GE, et al., “SEMAC: Slice encoding for metal artifact correction in MRI,” Magn Reson Med, vol. 62, pp. 66-76, 2009, https://doi.org/10.1002/mrm.21967 [doi]
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3. Galley J, Sutter R, Stern C, et al., “Diagnosis of Periprosthetic Hip Joint Infection Using MRI with Metal Artifact Reduction at 1.5 T,” Radiology, vol. 296, no. 1, pp. 98-108, 2020, doi: 10.1148/radiol.2020191901 [doi]
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Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/566-05-002