Niek RF Huttinga1, Tom Bruijnen1, Cornelis AT van den Berg1, and Alessandro Sbrizzi1
1Department of Radiotherapy, Computational Imaging Group for MR therapy & Diagnostics, University Medical Center Utrecht, Utrecht, Netherlands
1Department of Radiotherapy, Computational Imaging Group for MR therapy & Diagnostics, University Medical Center Utrecht, Utrecht, Netherlands
We present a probabilistic framework to perform joint real-time 3D motion estimation and uncertainty quantification at 67Hz frame-rate. Results show high quality predictions, and uncertainty estimates that could be used for real-time quality assurance during MR-guided radiotherapy.
Fig. 4: The spatial uncertainty as the standard deviations in the motion-fields, obtained from Eq. (3) and the GP predictions. The top rows shows motion-fields in left-right direction, the middle row anterior-posterior, and the bottom row the feet-head. The visualization shows dynamics from right before and during the bulk motion. It can be observed that the GP is highly confident before the bulk motion, that uncertainties increase during bulk motion, and that the initial confidence is partially regained afterwards.
Fig. 2: Visualization of motion-fields reconstructed with MR-MOTUS (Eq. (2)). Data was acquired on an MR-LINAC, with an 8-element radiolucent receive array, and a 3D golden-mean radial kooshball acquisition interleaved every 31 spokes with three orthogonal spokes along AP, LR, and FH. The temporal-subspace was constrained to a 1D motion surrogate that was extracted as the principal component of the three mutually orthogonal spokes along the time dimension[6]. This results in a spatial representation basis $$$\Phi$$$ that relates 3D+t motion-fields to a 1D motion surrogate.
