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相关概念视频

Computed Tomography01:10

Computed Tomography

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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...
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相关实验视频

Updated: May 1, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

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在使用深度学习的脏CT成像中基于细分的定量测量.

Konstantinos Koukoutegos1,2, Richard 's Heeren3, Liesbeth De Wever3

  • 1KU Leuven, Department of Imaging and Pathology, Division of Medical Physics, Herestraat 49, 3000, Leuven, Belgium. konstantinos.koukoutegos@uzleuven.be.

European radiology experimental
|October 9, 2024
PubMed
概括
此摘要是机器生成的。

深度学习从CT扫描中准确地测量脏,匹配人类的性能. 这种人工智能工具从对比度增强和非对比度图像提供快速,精确的脏测量,帮助临床决策.

关键词:
这里是 Abdomen Abdomen 的意思.人工智能的人工智能是人工智能.深度学习是一种深度学习.脏 - 脏 - 脏断层扫描 (X射线计算) 的使用

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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

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相关实验视频

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Deep Learning-Based Segmentation of Cryo-Electron Tomograms

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科学领域:

  • 放射学 放射学是一门学科.
  • 人工智能的人工智能
  • 医疗成像医学成像

背景情况:

  • 脏定量测量对于评估脏功能至关重要.
  • 需要从计算机断层扫描 (CT) 图像中自动测量脏.

研究的目的:

  • 开发和验证一种基于深度学习的方法,用于从CT图像进行自动脏测量.
  • 评估深度学习网络在细分和测量脏方面的表现.

主要方法:

  • 两个深度学习网络使用来自潜在脏捐赠者的对比增强和非对比CT扫描数据集进行了训练和验证.
  • 用子相似系数 (DSC) 评估细分性能.
  • 量化测量准确性与使用类内相关系数 (ICC) 的手册注释进行了比较.

主要成果:

  • 深度学习模型在各种CT数据集中实现了优异的细分可靠性,DSC得分高于0.92.
  • 卷值估计误差很低,平均为4-7%mL,对比度增强和非对比度扫描均为4-7%.
  • 轴测量显示出高精度,ICC值大于0.90.

结论:

  • 深度学习网络可以自动从对比增强和非对比CT成像中获得定量脏测量,以人类性能水平.
  • 这些人工智能模型提供准确,快速和专家级的脏测量,增强临床决策.
  • 模型适应需要仔细考虑,当应用到有不健康脏的数据集时.