TY - JOUR
T1 - Artificial intelligence in four-dimensional imaging for motion management in radiation therapy
AU - Yinghui, Wang
AU - Haonan, Xiao
AU - Jing, Wang
AU - Lu, Wang
AU - Wen, Li
AU - Zhuoran, Jiang
AU - Ge, Ren
AU - Shaohua, Zhi
AU - Josh, Qian
AU - Jianrong, Dai
AU - Kuo, Men
AU - Lei, Ren
AU - Xiaofeng, Yang
AU - Tian, Li
AU - Jing, Cai
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/1
Y1 - 2025/1
N2 - Four-dimensional imaging (4D-imaging) plays a critical role in achieving precise motion management in radiation therapy. However, challenges remain in 4D-imaging such as a long imaging time, suboptimal image quality, and inaccurate motion estimation. With the tremendous success of artificial intelligence (AI) in the image domain, particularly deep learning, there is great potential in overcoming these challenges and improving the accuracy and efficiency of 4D-imaging without the need for hardware modifications. In this review, we provide a comprehensive overview of how these AI-based methods could drive the evolution of 4D-imaging for motion management. We discuss the inherent issues associated with multiple 4D modalities and explore the current research progress of AI in 4D-imaging. Furthermore, we delve into the unresolved challenges and limitations in 4D-imaging and provide insights into the future direction of this field.
AB - Four-dimensional imaging (4D-imaging) plays a critical role in achieving precise motion management in radiation therapy. However, challenges remain in 4D-imaging such as a long imaging time, suboptimal image quality, and inaccurate motion estimation. With the tremendous success of artificial intelligence (AI) in the image domain, particularly deep learning, there is great potential in overcoming these challenges and improving the accuracy and efficiency of 4D-imaging without the need for hardware modifications. In this review, we provide a comprehensive overview of how these AI-based methods could drive the evolution of 4D-imaging for motion management. We discuss the inherent issues associated with multiple 4D modalities and explore the current research progress of AI in 4D-imaging. Furthermore, we delve into the unresolved challenges and limitations in 4D-imaging and provide insights into the future direction of this field.
KW - 4D-imaging
KW - Artificial intelligence
KW - Radiation therapy motion management
UR - https://www.scopus.com/pages/publications/85217276466
U2 - 10.1007/s10462-025-11109-w
DO - 10.1007/s10462-025-11109-w
M3 - Journal article
AN - SCOPUS:85217276466
SN - 0269-2821
VL - 58
JO - Artificial Intelligence Review
JF - Artificial Intelligence Review
IS - 4
M1 - 103
ER -