Magnetic resonance imaging (MRI) has significantly benefited from the resurgence of artificial intelligence (AI). By leveraging AI's capabilities in large-scale optimization and pattern recognition, innovative methods are transforming the MRI acquisition workflow, including planning, sequence design, and correction of acquisition artifacts. These emerging algorithms demonstrate substantial potential in enhancing the efficiency and throughput of acquisition steps. This review discusses several pivotal AI-based methods in neuro MRI acquisition, focusing on their technological advances, impact on clinical practice, and potential risks.
@article{arxiv.2406.05982,
title = {Artificial Intelligence for Neuro MRI Acquisition: A Review},
author = {Hongjia Yang and Guanhua Wang and Ziyu Li and Haoxiang Li and Jialan Zheng and Yuxin Hu and Xiaozhi Cao and Congyu Liao and Huihui Ye and Qiyuan Tian},
journal= {arXiv preprint arXiv:2406.05982},
year = {2024}
}