Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generalising Deep Learning MRI Reconstruction across Different Domains   We look into robustness of deep learning based MRI reconstruction when tested
on unseen contrasts and organs. We then propose to generalise the network by
training with large publicly-available natural image datasets with synthesised
phase information to achieve high cross-domain reconstruction performance which
is competitive with domain-specific training. To explain its generalisation
mechanism, we have also analysed patch sets for different training datasets.

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The categories of this paper are: gr-qc
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
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The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
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The categories of this paper are: math
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The categories of this paper are: hep-ex
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The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th