Multi-modal Magnetic Resonance Imaging (MRI) plays an important role in clinical medicine. However, the acquisitions of some modalities, such as the T2-weighted modality, need a long time and they are always accompanied by motion artifacts. On the other hand, the T1-weighted image (T1WI) shares the same underlying information with T2-weighted image (T2WI), which needs a shorter scanning time. Therefore, in this paper we accelerate the acquisition of the T2WI by introducing the auxiliary modality (T1WI). Concretely, we first reconstruct high-quality T2WIs with under-sampled T2WIs. Here, we realize fast T2WI reconstruction by reducing the sampling rate in the k-space. Second, we establish a cross-modal synthesis task to generate the synthetic T2WIs for guiding better T2WI reconstruction. Here, we obtain the synthetic T2WIs by decomposing the whole cross-modal generation mapping into two OT processes, the spatial alignment mapping on the T1 image manifold and the cross-modal synthesis mapping from aligned T1WIs to T2WIs. It overcomes the negative transfer caused by the spatial misalignment. Then, we prove the reconstruction and the synthesis tasks are well complementary. Finally, we compare it with state-of-the-art approaches on an open dataset FastMRI and an in-house dataset to testify the validity of the proposed method.

翻译：多模态磁共振成像（MRI）在临床医学中发挥着重要作用。然而，部分模态（如T2加权模态）的采集耗时长，且常伴随运动伪影。另一方面，T1加权图像（T1WI）与所需扫描时间较短的T2加权图像（T2WI）共享相同的底层信息。因此，本文通过引入辅助模态（T1WI）来加速T2WI的采集。具体而言，我们首先利用欠采样的T2WI重建高质量T2WI，通过降低k空间采样率实现快速T2WI重建。其次，建立跨模态合成任务以生成合成T2WI，从而指导更优的T2WI重建。在此过程中，我们将整个跨模态生成映射分解为两个最优传输（OT）过程：T1图像流形上的空间对齐映射，以及从对齐T1WI到T2WI的跨模态合成映射，从而克服空间错位引起的负迁移。随后，我们验证了重建与合成任务具有良好互补性。最后，在公开数据集FastMRI和内部数据集上，将所提方法与前沿方法进行比较，验证了其有效性。