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.

我们提供了一个标准化、多样化和高质量的 CMRxRecon2024 数据集，旨在促进心脏磁共振成像技术的发展和临床应用，实现快速和可靠的图像重建。