Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unsupervised Multi-Modal Medical Image Registration via
  Discriminator-Free Image-to-Image Translation   In clinical practice, well-aligned multi-modal images, such as Magnetic
Resonance (MR) and Computed Tomography (CT), together can provide complementary
information for image-guided therapies. Multi-modal image registration is
essential for the accurate alignment of these multi-modal images. However, it
remains a very challenging task due to complicated and unknown spatial
correspondence between different modalities. In this paper, we propose a novel
translation-based unsupervised deformable image registration approach to
convert the multi-modal registration problem to a mono-modal one. Specifically,
our approach incorporates a discriminator-free translation network to
facilitate the training of the registration network and a patchwise contrastive
loss to encourage the translation network to preserve object shapes.
Furthermore, we propose to replace an adversarial loss, that is widely used in
previous multi-modal image registration methods, with a pixel loss in order to
integrate the output of translation into the target modality. This leads to an
unsupervised method requiring no ground-truth deformation or pairs of aligned
images for training. We evaluate four variants of our approach on the public
Learn2Reg 2021 datasets \cite{hering2021learn2reg}. The experimental results
demonstrate that the proposed architecture achieves state-of-the-art
performance. Our code is available at https://github.com/heyblackC/DFMIR.

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The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
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The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
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The categories of this paper are: eess
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The categories of this paper are: comp-gas
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The categories of this paper are: chao-dyn
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The categories of this paper are: stat
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The categories of this paper are: ao-sci
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The categories of this paper are: gr-qc