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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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人工智能在干预放射学中的应用.

Carolina Lanza1, Salvatore Alessio Angileri1, Serena Carriero1

  • 1Department of Health Services, Diagnostic and Interventional Radiology, Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy.

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概括
此摘要是机器生成的。

人工智能 (AI) 通过改进规划,导航和评估来增强干预放射学 (IR). 像放射学,虚拟现实和人工智能驱动的成像工具等技术正在改变IR程序,以获得更好的结果.

关键词:
人工智能 (AI) 是一种人工智能.干预性放射学 (IR) 干预性放射学无线电学 (radiomics) 是一种无线电学.机器人技术 机器人工程 机器人工程三维 (3D) 建模虚拟现实 (VR) 是一种虚拟现实.

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科学领域:

  • 医学成像和干预性放射学
  • 人工智能在医学中的应用

背景情况:

  • 干预性放射学 (IR) 程序越来越复杂.
  • 集成先进技术对于改善IR结果至关重要.
  • 人工智能 (AI) 具有显著的潜力,可以增强IR的各个方面.

研究的目的:

  • 为人工智能在干预放射学中的当前应用和未来潜力提供全面的概述.
  • 分析影响IR的关键人工智能驱动技术,包括放射学,虚拟现实,机器人,融合成像和圆束计算断层扫描 (CBCT).

主要方法:

  • 过去几十年出版物的文献综述.
  • 分析与IR相关的AI相关领域的技术发展.
  • 检查AI在程序前规划,程序内导航和程序后评估中的作用.

主要成果:

  • 人工智能显著改善了IR的程序前规划,程序内导航和程序后评估.
  • 放射学可以通过图像特征提取实现个性化的治疗策略.
  • 虚拟现实为训练和模拟提供了先进的工具.
  • 由人工智能驱动的机器人系统提高了精度,并减少了辐射暴露.
  • 人工智能增强的融合成像和CBCT改善了实时指导和结果.

结论:

  • 人工智能是干预放射学的转型技术,在整个程序工作流程中提供了实质性的改进.
  • 人工智能与放射学,虚拟现实,机器人技术和先进成像等工具的整合是提高IR精度,安全性和有效性的关键.
  • 人工智能领域的持续研究和开发将进一步彻底改变IR实践和患者护理.