利用深度学习网络和 RE-WAPICP 算法进行混合现实中的协同诊断

IF 4.1 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Jiann-Der Lee , Jong-Chih Chien , Kuan-Chen Wang , Chieh-Tsai Wu
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引用次数: 0

摘要

这项研究探讨了混合现实技术在协作诊断中的应用,即多名医生使用头戴式显示器(HMD)设备实时共享医疗数据。对象检测和数字化数据与对象的对齐是任何混合现实应用的支柱。本文使用深度学习网络检测物理世界中患者的面部,并通过区域增强-重量-扰动迭代-闭合点(RE-WAPICP)算法将医疗数据与患者对齐。实验是通过在混合现实环境中与多人共享脑内血管的三维数字模型进行的,结果表明这种方法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Collaborative diagnosis in mixed-reality using deep-learning networks and RE-WAPICP algorithm

This investigation explores the use of mixed-reality in collaborative diagnosis by sharing medical data in real-time between multiple physicians using Head-Mounted Display (HMD) devices. Object detection and alignment of the digitized data with the object are the backbone in any mixed-reality application. In this paper, deep-learning networks are used in detecting the patient’s face in the physical world and the medical data is aligned to the patient via the Region-Enhanced-Weight-and-Perturb Iterative-Closest-Point (RE-WAPICP) algorithm. Experiments were performed by sharing a 3D digital model of intracerebral vascular with multi-viewers in a mix-reality environment and the results show that this approach is feasible.

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来源期刊
ICT Express
ICT Express Multiple-
CiteScore
10.20
自引率
1.90%
发文量
167
审稿时长
35 weeks
期刊介绍: The ICT Express journal published by the Korean Institute of Communications and Information Sciences (KICS) is an international, peer-reviewed research publication covering all aspects of information and communication technology. The journal aims to publish research that helps advance the theoretical and practical understanding of ICT convergence, platform technologies, communication networks, and device technologies. The technology advancement in information and communication technology (ICT) sector enables portable devices to be always connected while supporting high data rate, resulting in the recent popularity of smartphones that have a considerable impact in economic and social development.
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