Feb. 9, 2024, 5:46 a.m. | Xia Li Fabian Zhang Muheng Li Damien Weber Antony Lomax Joachim Buhmann Ye Zhang

cs.CV updates on arXiv.org arxiv.org

Intra-fraction motion in radiotherapy is commonly modeled using deformable image registration (DIR). However, existing methods often struggle to balance speed and accuracy, limiting their applicability in clinical scenarios. This study introduces a novel approach that harnesses Neural Graphics Primitives (NGP) to optimize the displacement vector field (DVF). Our method leverages learned primitives, processed as splats, and interpolates within space using a shallow neural network. Uniquely, it enables self-supervised optimization at an ultra-fast speed, negating the need for pre-training on extensive …

accuracy balance clinical cs.cv extraction fly graphics image neural graphics novel physics.med-ph registration speed struggle study vector

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