Author: Mok, Tony C. W.; Chung, Albert C. S.
Title: Large Deformation Image Registration with Anatomy-Aware Laplacian Pyramid Networks Cord-id: mjbm6nw2 Document date: 2021_2_23
ID: mjbm6nw2
Snippet: Deep learning-based methods have recently demonstrated remarkable results in deformable image registration for a wide range of medical image analysis tasks. However, most of the deep learning-based approaches are often limited to small deformation settings. In this paper, we describe a deformable image registration approach for the Learn2Reg 2020 challenge based on the Laplacian pyramid image registration networks. Our approach won 1st place in the Learn2Reg 2020 challenge.
Document: Deep learning-based methods have recently demonstrated remarkable results in deformable image registration for a wide range of medical image analysis tasks. However, most of the deep learning-based approaches are often limited to small deformation settings. In this paper, we describe a deformable image registration approach for the Learn2Reg 2020 challenge based on the Laplacian pyramid image registration networks. Our approach won 1st place in the Learn2Reg 2020 challenge.
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