在放射治疗中用于运动管理的四维成像中的人工智能
Wang Yinghui1, Xiao Haonan2, Wang Jing3
1Department of Health Technology and Informatics, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hong Kong 999077, Hong Kong SAR, China.
概括
人工智能 (AI) 可以显著改善放射治疗运动管理的四维成像 (4D成像). 人工智能在不需要硬件更改的情况下提高了准确性和效率,解决了当前4D成像的局限性.
科学领域:
- 医疗成像医学成像
- 辐射瘤学 辐射瘤学
- 人工智能的人工智能
背景情况:
- 四维成像 (4D成像) 对于辐射治疗中精确的运动管理至关重要.
- 当前的4D成像方法面临诸多挑战,包括漫长的扫描时间,图像质量差以及不准确的运动估计.
研究的目的:
- 提供人工智能 (AI) 应用在放射治疗的4D成像中的全面审查.
- 探索AI如何克服现有的局限性并增强运动管理.
- 讨论人工智能驱动的4D成像的未来方向和未解决的挑战.
主要方法:
- 关于人工智能和放射治疗中的4D成像现有文献的综述.
- 分析AI技术,特别是深度学习,应用于克服4D成像挑战.
- 讨论各种4D成像模式及其与AI的整合.
主要成果:
- 人工智能显示出在4D成像中提高准确性和效率的巨大潜力.
- 深度学习方法可以解决诸如长时间的成像时间和低于最佳的图像质量等问题.
- 人工智能为增强运动管理提供了一条途径,而不需要硬件修改.
结论:
- 基于人工智能的方法准备在放射治疗中彻底改变4D成像.
- 需要进一步的研究来解决剩余的挑战,并充分实现AI在这个领域的潜力.
- 通过改进的运动管理,人工智能集成有望实现更精确,更有效的癌症治疗.
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