从像素到病理学:利用计算机视觉解码医学图像中的胸部疾病
Muhammad Arslan1, Ali Haider2, Mohsin Khurshid3
1Department of Emergency Medicine, Royal Infirmary of Edinburgh, National Health Service (NHS) Lothian, Edinburgh, GBR.
Cureus
|October 23, 2023
概括
人工智能和机器学习正在改变放射学,通过CT扫描和X射线等先进的成像技术提高胸部疾病的检测能力. 需要进一步的研究来克服整合挑战,并最大限度地发挥这些诊断工具的临床益处.
科学领域:
- 放射学和医学成像学 医学成像学
- 医疗保健中的人工智能
- 诊断技术 诊断技术 诊断技术
背景情况:
- 放射学在过去30年中通过PACS和远程放射学进行了数字化转型.
- 新兴的人工智能和机器学习为综合诊断服务提供了潜力.
- 计算机辅助诊断 (CAD) 工具,包括深度学习CNN,已被开发用于医学图像分析.
研究的目的:
- 审查计算机辅助程序在推进胸部疾病检测中的作用.
- 检查人工智能对MRI,CXR,核医学和CT扫描的最新发展.
- 确定研究缺口,并探索将机器学习整合到诊断工具中.
主要方法:
- 综合文献综述,重点关注胸部疾病检测技术.
- 对计算机辅助程序和机器学习应用在放射学中的分析.
- 检查MRI,CXR,核医学和CT扫描成像方面的进展.
主要成果:
- CAD工具看起来有希望,但面临临临床整合挑战.
- 机器学习,特别是深度学习CNN,正在推进医学图像模式识别.
- 对人工智能进行了大量的研究,用于在各种成像方式中检测胸部疾病.
结论:
- 人工智能和机器学习具有显著的潜力,可以将放射学发展为综合诊断服务.
- 克服工作流集成和展示明显的临床益处对于CAD采用至关重要.
- 需要进一步的研究来完善人工智能算法,并促进它们无地纳入临床实践,以改善胸部疾病诊断.
关键词:
人工智能的人工智能是人工智能.胸部X射线 胸部X射线 胸部X射线计算机视觉 计算机视觉图像扫描仪扫描图像.损伤检测检测损伤的检测机器学习是机器学习.医学成像医学成像通过MRI进行MRI.核医学是核医学的一种.超声波超声波的使用情况.更多相关视频
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