医学成像中的大型模型:进展和前景
Mengjie Fang1,2, Zipei Wang1,3, Sitian Pan1,3
1Chinese Academy of Sciences Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Chinese medical journal
|June 20, 2025
概括
大型模型,包括大型语言模型和多式大型模型,通过提高诊断准确性和效率,正在改变医学成像. 需要进一步的研究,以克服广泛临床采用的挑战.
科学领域:
- 医疗保健中的人工智能
- 医学成像分析 医学成像分析
- 计算病理学计算病理学
背景情况:
- 大型模型显示出对医疗成像技术进行革命的前景.
- 这些模型为处理复杂的医疗数据提供了先进的功能.
- 目前的应用涵盖了各种成像方式和临床任务.
研究的目的:
- 审查医学成像中大型模型的概念,方法和进展.
- 突出大型模型在精准医学中的潜力.
- 确定临床实施的挑战和未来研究方向.
主要方法:
- 使用大型模型技术集成多式联运数据.
- 通过自我监督的预训和微调,通过医疗数据集训练大型模型.
- 利用交叉模式的表示学习来增强解释.
主要成果:
- 大型模型可以提高诊断准确性和工作流程效率.
- 潜在的应用包括图像细分,疾病诊断和个性化治疗.
- 成功实施需要解决数据稀缺和整合挑战.
结论:
- 大型模型为推进医学成像和精准医学提供了巨大的潜力.
- 克服与数据,安全和整合相关的挑战对于临床部署至关重要.
- 未来的研究应该专注于开发高效,可解释和可概括的模型.
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