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

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

Imaging Studies for Cardiovascular System III: X-Ray

169
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...
169

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

Prologue: Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 Annual Meeting.

The Journal of rheumatology·2026
Same authorSame journal

Externally Tested AI for Lung Nodule Classification: A Realistic Benchmark for an Emerging Screening Era.

Radiology. Artificial intelligence·2026
Same author

MHub.ai: A Standardized Platform for Reproducible AI Research in Medical Imaging.

Research square·2026
Same author

Reply.

Arthritis & rheumatology (Hoboken, N.J.)·2026
Same author

Efficacy of Ixekizumab in Radiographic Axial Spondyloarthritis by Baseline C-Reactive Protein Level: A Pooled Analysis of Phase III Trials.

Rheumatology and therapy·2026
Same author

Performing Best When Needed Least: Reader Experience Shapes Accuracy Gains in Large Language Model-assisted Brain MRI Differential Diagnosis.

Radiology·2026

相关实验视频

Updated: Jun 20, 2025

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

247

在标准DICOM和基于智能手机的胸部X射线图上用于心脏设备识别的开放数据和深度学习.

Felix Busch1, Keno K Bressem1, Phillip Suwalski1

  • 1From the Department of Radiology (F.B., L.H., S.M.N.), Department of Anesthesiology, Division of Operative Intensive Care Medicine (F.B.), Department of Cardiology (P.S.), and Department of Rheumatology (K.B.B., D.P., A.Z.), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, 12203 Berlin, Germany; Department of Radiology and Nuclear Medicine, German Heart Center, Technical University of Munich, Munich, Germany (K.K.B.); Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany (F.B., K.K.B., M.R.M., L.C.A.); Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, Mass (H.J.W.L.A.); Departments of Radiation Oncology and Radiology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, Mass (H.J.W.L.A.); and Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (H.J.W.L.A.).

Radiology. Artificial intelligence
|July 17, 2024
PubMed
概括

一个新的深度学习模型准确地对传统成像和智能手机的胸部X射线进行心脏植入式电子设备 (CIED) 的细分和分类. 这一进步有助于分析这些关键医疗设备.

关键词:
传统的X光学X光学分段化 分段化 分段化 分段化

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

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

Published on: November 30, 2022

2.7K
Author Spotlight: Customized Light-Sheet Imaging for Investigating Myocardial Structures in Rodent Hearts
05:58

Author Spotlight: Customized Light-Sheet Imaging for Investigating Myocardial Structures in Rodent Hearts

Published on: March 29, 2024

879

相关实验视频

Last Updated: Jun 20, 2025

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

247
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

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

Published on: November 30, 2022

2.7K
Author Spotlight: Customized Light-Sheet Imaging for Investigating Myocardial Structures in Rodent Hearts
05:58

Author Spotlight: Customized Light-Sheet Imaging for Investigating Myocardial Structures in Rodent Hearts

Published on: March 29, 2024

879

科学领域:

  • 医疗成像中的人工智能
  • 放射学和医学成像学 医学成像学
  • 心脏病学和心血管设备

背景情况:

  • 心脏植入式电子设备 (CIED) 对于管理心血管疾病至关重要.
  • 精确识别和分类的CIEDs在X线图上对于患者护理和设备管理至关重要.
  • 目前用于分析胸部X射线图上的CIED的现有方法可能在范围或可访问性方面存在限制.

研究的目的:

  • 开发和验证公开可访问的深度学习模型,用于对CIED进行细分和分类.
  • 评估模型在标准数字成像和医学通信 (DICOM) 和智能手机获得的胸部X射线图上的性能.
  • 为了实现各种CIED的自动化分析,包括心脏起器和除器.

主要方法:

  • 使用ResNet-50骨干的U-Net深度学习模型进行了训练和验证.
  • 这项研究使用了897名患者的2321张胸部X射线图和11,072张智能手机图像.
  • 根据制造商和型号对CIED进行分类,其性能以Dice系数来衡量细分和均衡准确度来进行分类.

主要成果:

  • 细分工具实现了0.936.9的高平均子系数.
  • 制造商分类准确率达到94.36%,而模型分类准确率为84.21%.
  • 该模型在DICOM和基于智能手机的胸部X射线图中表现出强大的性能.

结论:

  • 开发的深度学习模型准确地对胸部X射线图上CIED进行细分和分类.
  • 该模型在传统和智能手机图像上的有效性凸显了其广泛临床应用的潜力.
  • 该工具为心脏植入式电子设备的自动化分析提供了有前途的进步.