Suppr超能文献

关节镜检查中的无缝增强现实集成:关节重建与引导流程

Seamless augmented reality integration in arthroscopy: a pipeline for articular reconstruction and guidance.

作者信息

Shu Hongchao, Liu Mingxu, Seenivasan Lalithkumar, Gu Suxi, Ku Ping-Cheng, Knopf Jonathan, Taylor Russell, Unberath Mathias

机构信息

Department of Computer Science Johns Hopkins University Baltimore Maryland USA.

Department of Orthopedics Tsinghua Changgung Hospital Tsinghua University School of Medicine Beijing China.

出版信息

Healthc Technol Lett. 2025 Jan 10;12(1):e12119. doi: 10.1049/htl2.12119. eCollection 2025 Jan-Dec.

Abstract

Arthroscopy is a minimally invasive surgical procedure used to diagnose and treat joint problems. The clinical workflow of arthroscopy typically involves inserting an arthroscope into the joint through a small incision, during which surgeons navigate and operate largely by relying on their visual assessment through the arthroscope. However, the arthroscope's restricted field of view and lack of depth perception pose challenges in navigating complex articular structures and achieving surgical precision during procedures. Aiming at enhancing intraoperative awareness, a robust pipeline that incorporates simultaneous localization and mapping, depth estimation, and 3D Gaussian splatting (3D GS) is presented to realistically reconstruct intra-articular structures solely based on monocular arthroscope video. Extending 3D reconstruction to augmented reality (AR) applications, the solution offers AR assistance for articular notch measurement and annotation anchoring in a human-in-the-loop manner. Compared to traditional structure-from-motion and neural radiance field-based methods, the pipeline achieves dense 3D reconstruction and competitive rendering fidelity with explicit 3D representation in 7 min on average. When evaluated on four phantom datasets, our method achieves root-mean-square-error reconstruction error, peak signal-to-noise ratio and structure similarity index measure on average. Because the pipeline enables AR reconstruction and guidance directly from monocular arthroscopy without any additional data and/or hardware, the solution may hold the potential for enhancing intraoperative awareness and facilitating surgical precision in arthroscopy. The AR measurement tool achieves accuracy within and the AR annotation tool achieves a mIoU of 0.721.

摘要

关节镜检查是一种用于诊断和治疗关节问题的微创手术。关节镜检查的临床工作流程通常包括通过一个小切口将关节镜插入关节,在此过程中,外科医生主要依靠通过关节镜的视觉评估来进行操作。然而,关节镜有限的视野和缺乏深度感知能力,给在复杂关节结构中导航以及在手术过程中实现手术精度带来了挑战。为了增强术中的感知能力,提出了一种强大的流程,该流程结合了同步定位与地图构建、深度估计和三维高斯点云(3D GS),仅基于单目关节镜视频对关节内结构进行逼真的重建。将三维重建扩展到增强现实(AR)应用中,该解决方案以人在回路的方式为关节切迹测量和注释锚定提供AR辅助。与传统的基于运动结构和神经辐射场的方法相比,该流程平均在7分钟内就能实现密集的三维重建,并具有具有显式三维表示的有竞争力的渲染保真度。在四个体模数据集上进行评估时,我们的方法平均实现了均方根误差重建误差、峰值信噪比和结构相似性指数测量。由于该流程能够直接从单目关节镜进行AR重建和引导,无需任何额外的数据和/或硬件,该解决方案可能具有增强术中感知能力和提高关节镜手术精度的潜力。AR测量工具的精度在 以内,AR注释工具的平均交并比为0.721。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78e5/11730702/06159c4f4fc4/HTL2-12-e12119-g003.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验