Cardiac magnetic resonance imaging (MRI) has emerged as a clinically gold-standard technique for diagnosing cardiac diseases, thanks to its ability to provide diverse information with multiple modalities and anatomical views. Accelerated cardiac MRI is highly expected to achieve time-efficient and patient-friendly imaging, and then advanced image reconstruction approaches are required to recover high-quality, clinically interpretable images from undersampled measurements. However, the lack of publicly available cardiac MRI k-space dataset in terms of both quantity and diversity has severely hindered substantial technological progress, particularly for data-driven artificial intelligence. Here, we provide a standardized, diverse, and high-quality CMRxRecon2024 dataset to facilitate the technical development, fair evaluation, and clinical transfer of cardiac MRI reconstruction approaches, towards promoting the universal frameworks that enable fast and robust reconstructions across different cardiac MRI protocols in clinical practice. To the best of our knowledge, the CMRxRecon2024 dataset is the largest and most diverse publicly available cardiac k-space dataset. It is acquired from 330 healthy volunteers, covering commonly used modalities, anatomical views, and acquisition trajectories in clinical cardiac MRI workflows. Besides, an open platform with tutorials, benchmarks, and data processing tools is provided to facilitate data usage, advanced method development, and fair performance evaluation.

翻译：心脏磁共振成像（MRI）因其能够通过多种模态和解剖视角提供多样化信息，已成为诊断心脏疾病的临床金标准技术。加速心脏MRI被寄予厚望，以期实现时间高效且对患者友好的成像，而这需要先进的图像重建方法从欠采样测量中恢复出高质量、临床可解释的图像。然而，现有公开心脏MRI k空间数据集在数量和多样性方面的匮乏，严重阻碍了相关技术的实质性进步，特别是对于数据驱动的人工智能方法。为此，我们提供了一个标准化、多样化且高质量的CMRxRecon2024数据集，旨在促进心脏MRI重建方法的技术发展、公平评估与临床转化，从而推动能够在临床实践中不同心脏MRI协议下实现快速、稳健重建的通用框架的发展。据我们所知，CMRxRecon2024数据集是目前规模最大、多样性最丰富的公开心脏k空间数据集。它采集自330名健康志愿者，涵盖了临床心脏MRI工作流程中常用的模态、解剖视角和采集轨迹。此外，我们还提供了一个包含教程、基准测试和数据处理工具的开源平台，以促进数据使用、先进方法开发和公平的性能评估。