Catalán Tabita, Courdurier Matías, Osses Axel, Fotaki Anastasia, Botnar René, Sahli-Costabal Francisco, Prieto Claudia
Millennium Nucleus for Applied Control and Inverse Problems, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile.
Department of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile.
Comput Biol Med. 2025 Feb;185:109467. doi: 10.1016/j.compbiomed.2024.109467. Epub 2024 Dec 12.
Cardiac cine MRI is the gold standard for cardiac functional assessment, but the inherently slow acquisition process creates the necessity of reconstruction approaches for accelerated undersampled acquisitions. Several regularization approaches that exploit spatial-temporal redundancy have been proposed to reconstruct undersampled cardiac cine MRI. More recently, methods based on supervised deep learning have been also proposed to further accelerate acquisition and reconstruction. However, these techniques rely on usually large dataset for training, which are not always available and might introduce biases.
In this work we propose NF-cMRI, an unsupervised approach based on implicit neural field representations for cardiac cine MRI. We evaluate our method in in-vivo undersampled golden-angle radial multi-coil acquisitions for undersampling factors of 13x, 17x and 26x.
The proposed method achieves excellent scores in sharpness and robustness to artifacts and comparable or improved spatial-temporal depiction than state-of-the-art conventional and unsupervised deep learning reconstruction techniques.
We have demonstrated NF-cMRI potential for cardiac cine MRI reconstruction with highly undersampled data.
心脏电影磁共振成像（cMRI）是心脏功能评估的金标准，但固有的缓慢采集过程使得有必要采用重建方法来加速欠采样采集。已经提出了几种利用时空冗余的正则化方法来重建欠采样的心脏电影磁共振成像。最近，基于监督深度学习的方法也被提出来以进一步加速采集和重建。然而，这些技术通常依赖于大量的数据集进行训练，而这些数据集并不总是可用的，并且可能会引入偏差。
在这项工作中，我们提出了NF-cMRI，一种基于隐式神经场表示的用于心脏电影磁共振成像的无监督方法。我们在体内欠采样的黄金角径向多线圈采集中评估我们的方法，欠采样因子分别为13倍、17倍和26倍。
与现有的传统和无监督深度学习重建技术相比，所提出的方法在清晰度和对伪影的鲁棒性方面取得了优异的分数，并且在时空描绘方面具有可比性或得到了改进。
我们已经证明了NF-cMRI在使用高度欠采样数据进行心脏电影磁共振成像重建方面的潜力。
