Abstract
Magnetic resonance imaging-guided linear particle accelerators use reconstructed images to adapt the radiation beam to the tumor location. Image-based approaches are relatively slow, causing healthy tissue to be irradiated upon subject movement. This study targets on the use of con- volutional neural networks to estimate rigid patient movements directly from few acquired radial k-space lines. Thus, abrupt patient movements were simulated in image data of a head. De- pending on the number of acquired spokes after movement, the network quantiﰂed this motion precisely. These ﰂrst results suggest that neural network-based navigators can help accelerating beam guidance in radiotherapy.
Original language | English |
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Number of pages | 4 |
Publication status | Published - 2019 |
Event | Annual Meeting of the International Society of Magnetic Resonance in Medicine 2019 - Palais des congrès de Montréal, Montréal, Canada Duration: 11.05.2019 → 16.01.2021 |
Conference
Conference | Annual Meeting of the International Society of Magnetic Resonance in Medicine 2019 |
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Abbreviated title | ISMRM 2019 |
Country/Territory | Canada |
City | Montréal |
Period | 11.05.19 → 16.01.21 |
Research Areas and Centers
- Academic Focus: Biomedical Engineering