Patch-RegNet: a hierarchical deformable registration framework for inter-/intra-modality head-and-neck image registration with ViT-Morph

Yao Zhao; Xinru Chen; Brigid McDonald; Cenji Yu; Laurence E. Court; Tinsu Pan; He Wang; Xin Wang; Jack Phan; Jinzhong Yang

doi:10.1117/12.2653352

3 April 2023 Patch-RegNet: a hierarchical deformable registration framework for inter-/intra-modality head-and-neck image registration with ViT-Morph

Yao Zhao, Xinru Chen, Brigid McDonald, Cenji Yu, Laurence E. Court, Tinsu Pan, He Wang, Xin Wang, Jack Phan, Jinzhong Yang

Author Affiliations +

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 1246403 (2023) https://doi.org/10.1117/12.2653352
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

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.

Conference Presentation

Citation Download Citation

Yao Zhao, Xinru Chen, Brigid McDonald, Cenji Yu, Laurence E. Court, Tinsu Pan, He Wang, Xin Wang, Jack Phan, and Jinzhong Yang "Patch-RegNet: a hierarchical deformable registration framework for inter-/intra-modality head-and-neck image registration with ViT-Morph", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 1246403 (3 April 2023); https://doi.org/10.1117/12.2653352

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