基于人工智能的放射学在超声诊断中的应用和前景
Haoyan Zhang1,2, Zheling Meng1,2, Jinyu Ru1,2
1CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
Visual computing for industry, biomedicine, and art
|October 12, 2023
概括
基于人工智能 (AI) 的放射学通过分析各种成像类型来增强超声诊断. 这篇评论探讨了人工智能.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 超声波诊断 超声波诊断 超声波诊断
背景情况:
- 超声波成像提供了诸如高时间分辨率,低成本和无辐射等优势.
- 基于人工智能的放射学是医学成像分析的一个不断增长的领域.
- 超声波是许多临床应用中首选的方法.
研究的目的:
- 审查基于人工智能的放射学在超声波诊断中的现状和未来前景.
- 引入与放射学相关的各种超声波成像模式.
- 突出基于人工智能的放射学应用在静态,动态和多模式超声波分析中.
主要方法:
- 对基于人工智能的放射学和超声波现有文献的审查.
- 介绍成像方式:亮度模式超声波,色彩多普勒,弹性图像,对比增强超声波和多模式融合.
- 在不同类型的超声波数据中分析AI应用.
主要成果:
- 基于人工智能的放射学在提高超声波诊断精度方面显示出显著的潜力.
- 应用范围包括静态图像,动态视频和融合多模式数据.
- 各种超声波技术可以接受人工智能驱动的放射性分析.
结论:
- 基于人工智能的放射学是推动超声波诊断的有希望的前沿.
- 进一步的研究可以利用人工智能来释放超声数据的全部潜力.
- 人工智能与各种超声波模式的整合将提高临床效用.
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