甲状腺超声波中的人工智能
Chun-Li Cao1,2, Qiao-Li Li1,2, Jin Tong1
1Department of Ultrasound, The First Affiliated Hospital of Shihezi University, Shihezi, China.
Frontiers in oncology
|May 30, 2023
概括
人工智能 (AI) 和深度学习 (DL) 增强甲状腺超声波分析用于癌症查. 这些技术提高了诊断的准确性和效率,帮助放射科医生,减少了工作量.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 超声波技术 超声波技术 超声波技术
背景情况:
- 甲状腺癌发病率上升需要有效的诊断工具.
- 医生在解释甲状腺超声波中的工作量正在增加.
- 人工智能 (AI) 在医学图像分析方面表现有前途.
研究的目的:
- 在甲状腺超声波中提供AI和深度学习 (DL) 的全面概述.
- 讨论AI在诊断甲状腺疾病中的临床应用.
- 探索AI在区分良性/恶性结节和预测转移中的作用.
主要方法:
- 传统的机器学习 (ML) 和深度学习 (DL) 算法的审查.
- 分析甲状腺超声波成像中的AI应用.
- 专注于结节分类和转移预测.
主要成果:
- 人工智能在医学图像的定量评估方面显示出巨大潜力.
- 在超声波中,DL算法越来越多地被用于提高精度和效率.
- 人工智能有助于区分良性和恶性甲状腺结节.
结论:
- 人工智能技术对提高甲状腺疾病超声波诊断精度具有很大的前景.
- 人工智能可以显著减少放射科医生在甲状腺癌查中的工作量.
- 人工智能在甲状腺超声波成像中的未来前景是巨大的.
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