Patch-RegNet: A Hierarchical Deformable Registration Framework for Inter-/intra-modality head-and-neck image registration with ViT-Morph

Deformable image registration (DIR) between Computed Tomography (CT)/Magnetic Resonance (MR) or MR/MR images is fundamentally important for MR-guided adaptive radiotherapy. In this work, we propose a novel hierarchical DIR framework, Patch-RegNet, to achieve accurate and rapid CT/MR and MR/MR registration for head-and-neck cancer. Patch-RegNet includes three steps: a whole volume rigid registration, a patch-based rigid registration, and a patch-based DIR. An innovative deep-learning-based network, ViT-Morph, is developed for the patch-based DIR in Patch-RegNet, taking advantage of both CNN-based local features and long-range image relationships from Transformer. Our Patch-RegNet is demonstrated to achieve notably improved registration accuracy for both inter- and intra-modality registration