Cardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matching. Furthermore, extra efforts to deal with respiratory and cardiac motion by triggering and gating further increase the scan time. Several techniques have been developed to speed up CMR acquisitions, which usually acquire less data than that required by the Nyquist–Shannon sampling theorem, followed by regularized reconstruction to mitigate undersampling artefacts. Recent advances in CMR parametric mapping speed up CMR by synergistically exploiting spatial–temporal and contrast redundancies. In this article, we will review the recent developments in multi-contrast CMR image reconstruction for parametric mapping with special focus on low-rank and model-based reconstructions. Deep learning-based multi-contrast reconstruction has recently been proposed in other magnetic resonance applications. These developments will be covered to introduce the general methodology. Current technical limitations and potential future directions are discussed.

This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.

心脏磁共振成像（CMR）是多种心血管疾病无创诊断的重要工具。具有多对比 CMR 的参数映射能够量化心肌疾病的组织变化，并有望改善患者护理。然而，磁共振成像本质上是一种缓慢的成像方式，导致参数映射的采集时间很长，参数映射采集一系列具有不同对比度的心脏图像以进行信号拟合或字典匹配。此外，通过触发和门控处理呼吸和心脏运动的额外努力进一步增加了扫描时间。已经开发了几种技术来加速 CMR 采集，这些技术通常采集的数据少于 Nyquist-Shannon 采样定理所需的数据，然后是正则化重建以减轻欠采样伪影。CMR 参数映射的最新进展通过协同利用时空和对比度冗余来加速 CMR。在本文中，我们将回顾用于参数映射的多对比度 CMR 图像重建的最新进展，特别关注低秩和基于模型的重建。最近在其他磁共振应用中提出了基于深度学习的多对比度重建。将介绍这些发展以介绍一般方法。讨论了当前的技术限制和潜在的未来方向。我们将回顾用于参数映射的多对比度 CMR 图像重建的最新进展，特别关注低秩和基于模型的重建。最近在其他磁共振应用中提出了基于深度学习的多对比度重建。将介绍这些发展以介绍一般方法。讨论了当前的技术限制和潜在的未来方向。我们将回顾用于参数映射的多对比度 CMR 图像重建的最新进展，特别关注低秩和基于模型的重建。最近在其他磁共振应用中提出了基于深度学习的多对比度重建。将介绍这些发展以介绍一般方法。讨论了当前的技术限制和潜在的未来方向。

本文是主题问题“协同断层扫描图像重建：第 1 部分”的一部分。