Suppr超能文献

利用无标记针跟踪和成像数据叠加的混合现实活检导航系统。

Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition.

作者信息

Trojak Michał, Stanuch Maciej, Kurzyna Marcin, Darocha Szymon, Skalski Andrzej

机构信息

Department of Measurement and Electronics, AGH University of Krakow, 30-059 Krakow, Poland.

MedApp S.A., 30-150 Krakow, Poland.

出版信息

Cancers (Basel). 2024 May 16;16(10):1894. doi: 10.3390/cancers16101894.

Abstract

Exact biopsy planning and careful execution of needle injection is crucial to ensure successful procedure completion as initially intended while minimizing the risk of complications. This study introduces a solution aimed at helping the operator navigate to precisely position the needle in a previously planned trajectory utilizing a mixed reality headset. A markerless needle tracking method was developed by integrating deep learning and deterministic computer vision techniques. The system is based on superimposing imaging data onto the patient's body in order to directly perceive the anatomy and determine a path from the selected injection site to the target location. Four types of tests were conducted to assess the system's performance: measuring the accuracy of needle pose estimation, determining the distance between injection sites and designated targets, evaluating the efficiency of material collection, and comparing procedure time and number of punctures required with and without the system. These tests, involving both phantoms and physician participation in the latter two, demonstrated the accuracy and usability of the proposed solution. The results showcased a significant improvement, with a reduction in number of punctures needed to reach the target location. The test was successfully completed on the first attempt in 70% of cases, as opposed to only 20% without the system. Additionally, there was a 53% reduction in procedure time, validating the effectiveness of the system.

摘要

精确的活检规划和仔细的针注射操作对于确保按最初预期成功完成手术并将并发症风险降至最低至关重要。本研究介绍了一种解决方案,旨在帮助操作人员利用混合现实头戴设备沿着预先规划的轨迹精确地定位针。通过整合深度学习和确定性计算机视觉技术,开发了一种无标记针跟踪方法。该系统基于将成像数据叠加到患者身体上,以便直接感知解剖结构并确定从选定的注射部位到目标位置的路径。进行了四种类型的测试来评估该系统的性能:测量针位姿估计的准确性、确定注射部位与指定目标之间的距离、评估材料采集的效率,以及比较使用和不使用该系统时所需的手术时间和穿刺次数。这些测试,包括使用模型以及后两项测试中有医生参与,证明了所提出解决方案的准确性和可用性。结果显示有显著改善,到达目标位置所需的穿刺次数减少。70% 的病例第一次尝试就成功完成了测试,而没有该系统时只有20%。此外,手术时间减少了53%,验证了该系统的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de48/11119171/81c1c73470b5/cancers-16-01894-g001.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