Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Computed Tomography01:10

Computed Tomography

7.6K
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...
7.6K
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

671
Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
671
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

973
Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
973
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

893
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
893

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Feasibility and reliability of home spirometry in lymphangioleiomyomatosis.

Annals of the American Thoracic Society·2026
Same author

Beyond the Image Frame: An Art-Based Pedagogical Framework for Teaching Diagnostic Reasoning in Breast Ultrasound to Medical Students.

Diagnostics (Basel, Switzerland)·2026
Same author

Automated artificial intelligence detection of early or under-diagnosed interstitial lung disease by computed tomography in the COPDGene trial.

Respiratory medicine·2025
Same author

Lung Cancer-Like Presentation of Pulmonary Vein Stenosis After Radiofrequency Catheter Ablation for Atrial Fibrillation.

Respirology case reports·2025
Same author

Multi-modal machine learning classifier for idiopathic pulmonary fibrosis predicts mortality in interstitial lung diseases.

Respiratory investigation·2025
Same author

Cost-effectiveness of novel diagnostic tools for idiopathic pulmonary fibrosis in the United States.

BMC health services research·2025

相关实验视频

Updated: May 7, 2026

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
11:31

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Published on: May 20, 2016

10.7K

计算机断层扫描机器学习分类器与间歇性肺病死亡率相关.

Onofre Moran-Mendoza1, Abhishek Singla2, Angad Kalra3

  • 1Interstitial Lung Diseases Program, Division of Respirology and Sleep Medicine, Queen's University, 102 Stuart Street, Kingston, Ontario, K7L 2V7, Canada.

Respiratory investigation
|May 21, 2024
PubMed
概括

Fibresolve机器学习系统使用CT扫描预测间歇性肺部疾病 (ILD) 的死亡率. 这种工具提供了与GAP得分相似的预后性能,有助于预测患者的结果.

关键词:
人工智能的人工智能是人工智能.异形性肺纤维化症 异形性肺纤维化症间歇性肺病 间歇性肺病机器学习是机器学习.

更多相关视频

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
04:44

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease

Published on: June 16, 2020

19.9K
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

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

Published on: December 19, 2020

14.1K

相关实验视频

Last Updated: May 7, 2026

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
11:31

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Published on: May 20, 2016

10.7K
Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
04:44

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease

Published on: June 16, 2020

19.9K
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

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

Published on: December 19, 2020

14.1K

科学领域:

  • 肺部医学 肺部医学
  • 放射学 放射学是一门学科.
  • 医疗保健中的人工智能

背景情况:

  • 异形性肺纤维化 (IPF) 诊断通常需要侵入性手术.
  • 开发了一种新的机器学习系统Fibresolve,用于使用胸部CT成像进行IPF的非侵入性诊断.
  • 该研究调查了Fibresolve作为间歇性肺部疾病 (ILD) 中死亡率预测者的潜力.

研究的目的:

  • 评估Fibresolve分类器对IPF和其他ILD患者死亡率的预测值.
  • 为了比较Fibresolve的预测性能与既定的风险因素和评分系统.

主要方法:

  • 之前已经验证了Fibresolve,这是一种分析胸部CT扫描的深度学习算法.
  • 分析了一组228名患有ILD的患者和现有的随访数据.
  • 进行了考克斯回归分析,调整了性别,年龄和生理学 (GAP) 评分和其他死亡率预测指标.

主要成果:

  • 在平均2.8年的随访期间,发生了89例死亡.
  • 在调整了GAP得分和其他因素后,Fibresolve得分独立预测死亡风险 (HR:7.14;p=0.02).
  • 纤维溶解三角体也显著预测死亡风险 (p=0.027),高三角体显示增加的危险比率.

结论:

  • Fibresolve机器学习分类器是ILDs死亡率的独立预测器.
  • Fibresolve显示出与GAP分数相当的预后性能,仅使用CT成像.
  • 这种由人工智能驱动的工具提供了一种非侵入性方法,用于在ILD患者中进行风险分层.