MRI-guided radiation therapy (MRgRT) offers a precise and adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematically reviewed. MRI-guided radiation therapy offers a precise, adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematically reviewed with emphasis placed on underlying methods. Studies are further categorized into the areas of segmentation, synthesis, radiomics, and real time MRI. Finally, clinical implications, current challenges, and future directions are discussed.
@article{arxiv.2303.11378,
title = {Deep Learning in MRI-guided Radiation Therapy: A Systematic Review},
author = {Zach Eidex and Yifu Ding and Jing Wang and Elham Abouei and Richard L. J. Qiu and Tian Liu and Tonghe Wang and Xiaofeng Yang},
journal= {arXiv preprint arXiv:2303.11378},
year = {2023}
}