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相关概念视频

Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

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The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
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Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

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Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
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X-ray Imaging01:24

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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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相关实验视频

Updated: Jul 1, 2025

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
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Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

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使用模型组合在胸部X射线图像上进行可泛化的疾病检测.

Maider Abad1, Jordi Casas-Roma2,3,4, Ferran Prados2,5,6

  • 1Universitat Oberta de Catalunya, e-Health Center, Barcelona, Spain. mabdvz@uoc.edu.

Scientific reports
|March 12, 2024
PubMed
概括

这项研究评估了使用胸部X射线检测COVID-19的预训练卷积神经网络 (CNN) 模型. 整体方法显著提高了各种数据集的准确性,优于单个模型.

关键词:
域名适应领域适应整体分类器 集成分类器预先训练有素的模型.转移学习转移学习在X射线成像中使用X射线成像.

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Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
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Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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相关实验视频

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Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
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Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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科学领域:

  • 医疗成像医学成像
  • 医疗保健中的人工智能
  • 诊断工具 诊断工具

背景情况:

  • 越来越多的人对快速而准确的医疗保健诊断的需求.
  • 在医学图像分析中需要强大的AI模型.

研究的目的:

  • 分析预训练的卷积神经网络 (CNN) 架构 (ResNet50,DenseNet121,Inception-ResNet-v2) 的性能,用于从胸部X射线中检测COVID-19.
  • 评估不同数据集中的模型通用性.
  • 开发一个集体方法,以提高诊断准确度.

主要方法:

  • 策划了一个大规模的胸部X射线图像数据集 (COVID-19阳性和阴性病例).
  • 进行了ResNet50,DenseNet121和Inception-ResNet-v2.2.的内部和外部验证.
  • 开发了一种基于不确定性的集合方法,用于模型权重的.

主要成果:

  • 个别的CNN模型在外部验证数据集上显示了显著的准确性下降.
  • 丹斯网121实现了96.71%的准确性 (内部),Inception-ResNet-v2实现了76.70%的准确性 (外部).
  • 整体方法提高了准确度,达到97.38% (内部) 和81.18% (外部).

结论:

  • 预先训练有素的CNN在外部数据集上表现出较低的有效性.
  • 基于不确定性的整体方法有效地提高了诊断性能和通用性.
  • 合奏方法为可靠的人工智能驱动的COVID-19检测提供了一个有希望的解决方案.