Dual-Stream Pyramid Registration Network
- URL: http://arxiv.org/abs/1909.11966v2
- Date: Sat, 1 Apr 2023 11:28:05 GMT
- Title: Dual-Stream Pyramid Registration Network
- Authors: Miao Kang and Xiaojun Hu and Weilin Huang and Matthew R. Scott and
Mauricio Reyes
- Abstract summary: We propose a Dual-Stream Pyramid Registration Network (referred as Dual-PRNet) for unsupervised 3D medical image registration.
We design a two-stream architecture able to compute multi-scale registration fields from convolutional feature pyramids.
The proposed Dual-PRNet is evaluated on two standard benchmarks for brain MRI registration.
- Score: 34.65021683954268
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We propose a Dual-Stream Pyramid Registration Network (referred as
Dual-PRNet) for unsupervised 3D medical image registration. Unlike recent
CNN-based registration approaches, such as VoxelMorph, which explores a
single-stream encoder-decoder network to compute a registration fields from a
pair of 3D volumes, we design a two-stream architecture able to compute
multi-scale registration fields from convolutional feature pyramids. Our
contributions are two-fold: (i) we design a two-stream 3D encoder-decoder
network which computes two convolutional feature pyramids separately for a pair
of input volumes, resulting in strong deep representations that are meaningful
for deformation estimation; (ii) we propose a pyramid registration module able
to predict multi-scale registration fields directly from the decoding feature
pyramids. This allows it to refine the registration fields gradually in a
coarse-to-fine manner via sequential warping, and enable the model with the
capability for handling significant deformations between two volumes, such as
large displacements in spatial domain or slice space. The proposed Dual-PRNet
is evaluated on two standard benchmarks for brain MRI registration, where it
outperforms the state-of-the-art approaches by a large margin, e.g., having
improvements over recent VoxelMorph [2] with 0.683->0.778 on the LPBA40, and
0.511->0.631 on the Mindboggle101, in term of average Dice score. Code is
available at: https://github.com/kangmiao15/Dual-Stream-PRNet-Plus.
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