Jove
Visualize
联系我们

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

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

Deep learning for fluorescence confocal microscopy image interpretation in radical prostatectomy.

BJU international·2026
Same author

CRAC-DM: class relation-aware categorical diffusion model for surgical scene segmentation.

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

Interpretable classification of endomicroscopic brain data via saliency consistent contrastive learning.

Medical image analysis·2025
Same author

A case of fistulating disease involving the terminal ileum and sigmoid colon-A video vignette.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland·2025
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

相关实验视频

Updated: May 8, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.4K

闭塞-坚固的无标记手术仪器构成估计估计.

Haozheng Xu1, Stamatia Giannarou1

  • 1Hamlyn Centre for Robotic Surgery, Department of Surgery and Cancer Imperial College London London UK.

Healthcare technology letters
|December 25, 2024
PubMed
概括

这项研究引入了一种基于视觉的新框架,用于在机器人辅助微创手术 (RMIS) 中估计无标记手术仪器的姿势. 该方法实现了亚毫米精度,即使有部分可见性和遮.

科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 计算机视觉 计算机视觉
  • 手术技术 手术技术

背景情况:

  • 准确的手术仪器姿势估计对于机器人辅助微创手术 (RMIS) 导航和自主任务执行至关重要.
  • 目前的方法与部分可见性,遮和动态的外科环境作斗争,限制了它们的可靠性.

研究的目的:

  • 提出一个强大的,无标记,基于视觉的框架来估计手术仪器的6DoF姿势.
  • 为了应对部分可见性和手术场景中遮所带来的挑战.

主要方法:

  • 一个关键点对象表示与PNP解决器相结合,用于稳定和准确的姿势计算.
  • 一种基于面具的新型数据增强技术,用于改善模拟学习.
  • 创建一个具有高精度地面真相的新数据集,用于仪器立场估计.

主要成果:

  • 拟议的网络实现了仪器定位估计的亚毫米精度.
  • 实验结果表明,该框架在各种闭塞类型和外科手术仪器中具有普遍性.
  • 该系统有效地处理部分工具可见性和堵塞.

结论:

  • 开发的基于视觉的框架为RMIS中的无标记手术仪器体位估计提供了显著的改进.
关键词:
内镜的内镜是指内镜.医疗机器人 医疗机器人构成估计估计的估计.

更多相关视频

Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact
10:07

Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact

Published on: February 10, 2015

19.1K
A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
10:42

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

Published on: January 28, 2020

6.4K

相关实验视频

Last Updated: May 8, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.4K
Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact
10:07

Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact

Published on: February 10, 2015

19.1K
A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
10:42

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

Published on: January 28, 2020

6.4K
  • 这种方法增强了对诸如闭塞等常见挑战的强度,为更可靠的机器人手术铺平了道路.
  • 该方法显示了集成到现实世界手术导航和自主机器人系统的潜力.