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相关概念视频

Computed Tomography01:10

Computed Tomography

7.9K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.9K

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相关实验视频

Updated: Jan 7, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

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深度学习用于放射治疗中的CT合成.

Yike Guo1, Yi Luo1, Hamed Hooshangnejad1,2

  • 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA.

Bioengineering (Basel, Switzerland)
|December 30, 2025
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 深度学习 (DL) 方法正在通过生成合成CT (sCT) 图像来彻底改变放射瘤学. 这项技术增强了图像引导的自适应性放射治疗和无模拟的工作流程,改善了患者的护理.

关键词:
深度学习 (DL) 是指深度学习.辐射疗法 辐射疗法合成CT (sCT) 的使用.

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相关实验视频

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科学领域:

  • 辐射疗法 辐射疗法
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 深度学习 (DL) 方法越来越多地被整合到辐射瘤学中.
  • 合成计算机断层扫描 (sCT) 图像生成是一个关键的兴趣领域.
  • sCT支持先进的临床场景,如图像引导适应性放射治疗 (IGART) 和无模拟工作流.

研究的目的:

  • 在放射治疗中提供基于DL的sCT合成的全面审查.
  • 讨论各种成像模式的临床应用.
  • 检查DL模型架构和培训策略.

主要方法:

  • 关于基于DL的sCT合成的最近研究的综述.
  • 对卷积神经网络 (CNN) 和生成对抗网络 (GAN) 的分析.
  • 检查多模式成像输入 (CBCT,MRI,诊断CT).

主要成果:

  • 基于DL的sCT合成在多个临床应用中显示出显著的潜力.
  • 包括CNN和GAN在内的各种DL架构对于sCT生成是有效的.
  • 新兴的培训策略正在提高sCT的质量和临床适用性.

结论:

  • 人工智能驱动的sCT生成可以减少成像负担,并提高放射治疗中的剂量准确性.
  • 通过sCT加速工作流效率有潜力显著改善患者治疗结果.
  • 需要进一步的研究来解决DL算法的临床翻译方面的挑战.