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DSFormer: A Dual-domain Self-supervised Transformer for Accelerated Multi-contrast MRI Reconstruction. (arXiv:2201.10776v2 [eess.IV] UPDATED)
Aug. 18, 2022, 1:12 a.m. | Bo Zhou, Neel Dey, Jo Schlemper, Seyed Sadegh Mohseni Salehi, Chi Liu, James S. Duncan, Michal Sofka
cs.CV updates on arXiv.org arxiv.org
Multi-contrast MRI (MC-MRI) captures multiple complementary imaging
modalities to aid in radiological decision-making. Given the need for lowering
the time cost of multiple acquisitions, current deep accelerated MRI
reconstruction networks focus on exploiting the redundancy between multiple
contrasts. However, existing works are largely supervised with paired data
and/or prohibitively expensive fully-sampled MRI sequences. Further,
reconstruction networks typically rely on convolutional architectures which are
limited in their capacity to model long-range interactions and may lead to
suboptimal recovery of fine anatomical …
More from arxiv.org / cs.CV updates on arXiv.org
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