探索生成人工智能在医疗图像合成中的潜力:机遇,挑战和未来方向
Bardia Khosravi1, Saptarshi Purkayastha2, Bradley J Erickson3
1Department of Radiology, Mayo Clinic, Rochester, MN, USA; Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
The Lancet. Digital health
|August 15, 2025
概括
生成型人工智能 (AI) 创建现实的合成医学成像数据. 这项技术增强了研究多样性,隐私和应用,同时解决了未来临床使用的伦理挑战.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 自2022年以来,生成人工智能 (AI) 已经迅速发展.
- 由AI生成的合成数据集密切模仿真实世界的医疗数据.
- 人工智能在医学成像中的作用具有变革性,为研究提供了新的途径.
研究的目的:
- 检查医疗成像中合成数据的进展,应用和挑战.
- 探索用于增强医学研究资源的生成性AI范式.
- 讨论合成数据在临床翻译中的潜力和局限性.
主要方法:
- 对生成性AI图像生成范式的审查 (例如,基于物理的统计模型).
- 合成数据属性的分析:多样性,隐私保护,多功能性.
- 在医学教育,罕见病,放射学和合作中探索应用.
主要成果:
- 生成型人工智能能够创建多样化,保护隐私的合成医疗数据集.
- 合成数据可以模拟复杂的生物现象,并增强研究.
- 应用包括加强医疗教育,增加罕见病数据,改进放射学工作流程和保护隐私的多中心合作.
结论:
- 生成型人工智能为医学成像研究和应用提供了重大前景.
- 解决患者隐私,数据复制和偏见等挑战对于临床翻译至关重要.
- 未来的研究需要强大的评估框架和负责任的AI在医学成像中的利用.
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