A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learning
<|reference_start|>A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learning: Magnetic resonance imaging (MRI) is renowned for its exceptional soft tissue contrast and high spatial resolution, making it a pivotal tool in medical imaging. The integration of deep learning algorithms offers significant potential for optimizing MRI reconstruction processes. Despite the growing body of research in this area, a comprehensive survey of optimization-based deep learning models tailored for MRI reconstruction has yet to be conducted. This review addresses this gap by presenting a thorough examination of the latest optimization-based algorithms in deep learning specifically designed for MRI reconstruction. The goal of this paper is to provide researchers with a detailed understanding of these advancements, facilitating further innovation and application within the MRI community.<|reference_end|>
@article{bian2024a,
    title={A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction
  Using Deep Learning},
    author={Wanyu Bian},
    journal={arXiv preprint arXiv:2406.02626},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.02626},
    primaryClass={eess.IV cs.CV math.OC}
}