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

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

Intraoperative fusion of models and data for robust distance sensing.

International journal of computer assisted radiology and surgery·2026
Same author

Current validation practice undermines surgical AI development.

ArXiv·2026
Same author

Interdisciplinary Dialogues on Surgical Data Science: Revising Its Benefits for Surgical Stakeholders and Patients.

IEEE transactions on medical robotics and bionics·2026
Same author

A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on Behalf of the Stakeholder Taskforce for Artificial Intelligence-Assisted Robotic Thrombectomy (START).

Journal of the American Heart Association·2026
Same author

Domain-agnostic weakly supervised surgical instrument segmentation.

Scientific reports·2026
Same author

Robust Distance Estimation with Out-of-distribution Detection in Ophthalmic Surgery.

IEEE transactions on bio-medical engineering·2026

相关实验视频

Updated: Jul 2, 2025

A High-Throughput Image-Guided Stereotactic Neuronavigation and Focused Ultrasound System for Blood-Brain Barrier Opening in Rodents
08:02

A High-Throughput Image-Guided Stereotactic Neuronavigation and Focused Ultrasound System for Blood-Brain Barrier Opening in Rodents

Published on: July 16, 2020

4.8K

神经IGN:可解释的多模式图像引导系统,用于精确的脑瘤手术.

Ramy A Zeineldin1,2,3, Mohamed E Karar4, Oliver Burgert5

  • 1Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander University Erlangen-Nürnberg, 91052, Erlangen, Germany. ramy.zeineldin@fau.de.

Journal of medical systems
|February 23, 2024
PubMed
概括

一个新的多式影像导向神经外科 (IGN) 系统NeuroIGN使用深度学习和可解释的AI来改善脑瘤手术. 它提供了高精度和实时功能,增强了外科医生的信任,并可能改善患者的治疗结果.

关键词:
深度学习是一种深度学习.可以解释的可解释性.在 IGN IGN IGN 的位置上.这就是为什么MRI是MRI.神经导航是一种神经导航.这就是iUSUS.

更多相关视频

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.3K
Longitudinal Intravital Imaging of Brain Tumor Cell Behavior in Response to an Invasive Surgical Biopsy
09:17

Longitudinal Intravital Imaging of Brain Tumor Cell Behavior in Response to an Invasive Surgical Biopsy

Published on: May 3, 2019

7.4K

相关实验视频

Last Updated: Jul 2, 2025

A High-Throughput Image-Guided Stereotactic Neuronavigation and Focused Ultrasound System for Blood-Brain Barrier Opening in Rodents
08:02

A High-Throughput Image-Guided Stereotactic Neuronavigation and Focused Ultrasound System for Blood-Brain Barrier Opening in Rodents

Published on: July 16, 2020

4.8K
A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.3K
Longitudinal Intravital Imaging of Brain Tumor Cell Behavior in Response to an Invasive Surgical Biopsy
09:17

Longitudinal Intravital Imaging of Brain Tumor Cell Behavior in Response to an Invasive Surgical Biopsy

Published on: May 3, 2019

7.4K

科学领域:

  • 神经外科 神经外科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 精确的神经外科指导对于成功的脑外科手术至关重要.
  • 图像引导的神经外科 (IGN) 系统提供与虚拟患者模型相对的手术工具的实时跟踪.

研究的目的:

  • 开发一种使用深度学习和可解释的人工智能来增强脑瘤手术的新型多式IGN系统 (NeuroIGN).
  • 建立对脑瘤手术IGN系统的临床和技术要求.

主要方法:

  • 神经IGN具有模块化架构:脑瘤细分,患者注册和可解释的输出预测.
  • 该系统将开源软件包整合到一个交互式神经导航显示器中.
  • 在实验室和模拟操作室 (OR) 设置中验证了组件.

主要成果:

  • 该系统在瘤细分方面展示了准确性,ExplainAI提高了医疗专业人员对深度学习的信心.
  • 在11分钟内,NeuroIGN在临床前的OR中组装和设置,实现了0.5 (±0.1) 毫米的跟踪精度.
  • 该系统被评为非常有用,提供高率 (19 FPS) 和实时超声波成像.

结论:

  • 本文介绍了开源多式联网IGN系统的开发过程.
  • 这项研究强调了深度学习和可解释的AI在脑瘤手术的神经导航中的应用.
  • 神经IGN系统显示了改善脑瘤患者手术治疗和长期结果的潜力.