ORCID: https://orcid.org/0000-0002-5683-5889; Preibisch, Christine
ORCID: https://orcid.org/0000-0003-4067-1928 und Schnabel, Julia A.
(2023):
Physics-Aware Motion Simulation For T2*-Weighted Brain MRI.
8th International Workshop on Simulation and Synthesis in Medical Imaging (SASHIMI), Vancouver, Canada, 08. Oktober 2023.
Wolterink, Jelmer M.; Svoboda, David; Zhao, Can und Fernandez, Virginia (eds.) :
In: Simulation and Synthesis in Medical Imaging, Lecture Notes in Computer Science
Vol. 14288
Cham: Springer. pp. 42-52
Abstract
In this work, we propose a realistic, physics-aware motion simulation procedure for T *-weighted magnetic resonance imaging (MRI) to improve learning-based motion correction. As T *-weighted MRI is highly sensitive to motion-related changes in magnetic field inhomogeneities, it is of utmost importance to include physics information in the simulation. Additionally, current motion simulations often only assume simplified motion patterns. Our simulations, on the other hand, include real recorded subject motion and realistic effects of motion-induced magnetic field inhomogeneity changes. We demonstrate the use of such simulated data by training a convolutional neural network to detect the presence of motion in affected k-space lines. The network accurately detects motion-affected k-space lines for simulated displacements down to 0.5 mm (accuracy on test set: ). Finally, our results demonstrate exciting opportunities of simulation-based k-space line detection combined with more powerful reconstruction methods. Our code is publicly available at: https://github.com/HannahEichhorn/T2starLineDet.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Research Centers: | Munich Center for Neurosciences – Brain & Mind |
| Subjects: | 000 Computer science, information and general works > 004 Data processing computer science 600 Technology > 610 Medicine and health |
| ISBN: | 978-3-031-44688-7 ; 978-3-031-44689-4 ; 978-3-031-44690-0 |
| ISSN: | 0302-9743 |
| Place of Publication: | Cham |
| Language: | English |
| Item ID: | 123903 |
| Date Deposited: | 25. Feb 2025 16:03 |
| Last Modified: | 25. Feb 2025 16:03 |
