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

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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

Kyphotic Scapular Posture Increases Posterior Deltoid Demand and Acromial-Spine Strain During Shoulder Motion: A Cadaver Study.

Clinical orthopaedics and related research·2026
Same author

The Diagnostic Challenges of the Digitation Sign for Subscapularis Tears: Impact of Observer Expertise.

Arthroscopy, sports medicine, and rehabilitation·2026
Same author

Moderate to high levels of spin in studies comparing open and arthroscopic Latarjet procedures for anterior shoulder instability: A systematic review from the LaTour Group.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA·2026
Same author

Own the turf or lose it: Ultrasound-guided procedures and the future of shoulder repair.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA·2026
Same author

Comprehensive arthroscopic management versus total shoulder arthroplasty and hemiarthroplasty in patients with primary glenohumeral arthritis younger than 50 years old.

EFORT open reviews·2026
Same author

Muscle edema of the rotator cuff: a systematic review of characteristics and associated pathologies from the LaTour group.

EFORT open reviews·2026

相关实验视频

Updated: Jun 17, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
12:50

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

40.2K

深度学习算法使得基于MRI的头骨形态分析能够与基于CT的评估相提并论的值.

Hanspeter Hess1, Alexandra Oswald1, J Tomás Rojas2,3

  • 1Department of Orthopaedic Surgery and Traumatology, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.

Scientific reports
|January 10, 2025
PubMed
概括
此摘要是机器生成的。

深度学习可以从MRI扫描中进行准确的3D骨形态分析. 这种方法克服了传统成像技术的局限性,为预测旋转手腕伤风险提供了一种具有成本效益和无辐射的方法.

关键词:
人工智能 (AI) 是一种人工智能.核磁共振成像重建的重建规划 规划 规划预测模型是一个预测模型.旋转器袖口的旋转器袖口是什么在肩膀上进行手术.

更多相关视频

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

7.9K
A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging
11:50

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Published on: February 4, 2022

3.9K

相关实验视频

Last Updated: Jun 17, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
12:50

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

40.2K
Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

7.9K
A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging
11:50

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Published on: February 4, 2022

3.9K

科学领域:

  • 整形外科手术 整形外科手术
  • 医学成像医学成像
  • 人工智能的人工智能是人工智能.

背景情况:

  • 骨形态是旋转器袖口修复结果的潜在预后指标.
  • 当前像MRI这样的成像方法在准确度上有局限性,而CT扫描则涉及成本和辐射暴露.

研究的目的:

  • 开发和验证基于深度学习的方法,用于使用诊断型MRI进行自动化3D护甲状腺形态分析.
  • 为了克服MRI中异构分辨率和缩小视野的局限性,用于头骨分析.

主要方法:

  • 一个深度学习细分网络被训练使用CT-derived scapula数据.
  • 一个多平面细分融合算法生成了高分辨率的3D护甲模型.
  • 第二个深度学习网络分析了形态特征,如关键肩膀角度,角质倾斜和版本.

主要成果:

  • 与CT相比,提出的深度学习方法在测量关键肩膀角度 (-1.3±1.7°),状腺倾斜 (1.3±2.1°) 和状腺版本 (-1.4±3.4°) 中取得了高精度.
  • 在MRI和CT衍生的指标之间发现了实质性的或几乎完美的类间相关性.
  • 深度学习成功地解决了在MRI中减少分辨率,骨质对比度和视野的挑战.

结论:

  • 深度学习可以从标准诊断型MRI中进行准确的3D脚形态分析.
  • 这种方法为CT提供了一种可行的,无辐射的替代方案,用于评估旋转片修复成功的预后指标.