人工智能及其与诊断成像医学物理学家临床实践的潜在整合:一篇综述
Ngo Fung Daniel Lam1, Jing Cai2, Kwan Hoong Ng3,4
1Department of Radiology, Queen Mary Hospital, Pok Fu Lam, Hong Kong.
Physical and engineering sciences in medicine
|March 24, 2025
概括
人工智能 (AI) 可以帮助医学物理学家管理成像工作量的增加. 本综述探讨了将AI整合到医学物理实践中的AI技术,应用和挑战.
科学领域:
- 医学物理 医学物理
- 人工智能的人工智能
- 放射学 放射学是一门学科.
背景情况:
- 临床医学物理包括质量保证,图像分析,剂量测量,辐射保护和研究.
- 越来越复杂的医学成像技术正在导致物理学家的工作量增加.
- 人工智能 (AI) 在医学物理工作流程中的整合目前尚未得到充分探索.
研究的目的:
- 提供与医学物理学相关的AI技术的概述.
- 概述AI在医学物理成像中的潜在应用.
- 讨论阻碍临床AI采用的挑战和局限性.
主要方法:
- 对人工智能技术的文献综述.
- 分析AI在质量保证,图像处理,剂量测量和辐射保护方面的应用.
- 讨论临床实施的障碍.
主要成果:
- 人工智能提供了适用于各种医学物理任务的多种技术.
- 潜在的AI应用包括自动图像分析,剂量优化和风险预测.
- 仍然存在重大挑战,包括数据要求,验证和监管障碍.
结论:
- 人工智能对提高医疗物理效率和准确性有很大的承诺.
- 解决技术,道德和监管方面的挑战对于成功的AI集成至关重要.
- 需要进一步的研究和开发,才能在临床实践中实现AI的全部潜力.
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