Development of an inside-out augmented reality technique for neurosurgical navigation

增强现实 计算机视觉 人工智能 计算机科学 可视化 基准标记 渲染(计算机图形) 姿势 图像配准 计算机图形学(图像) 图像(数学)
作者
Yun‐Sik Dho,Sang Joon Park,Haneul Choi,Youngdeok Kim,Hyeong Cheol Moon,Kyung Min Kim,Ho Kang,Eun Jung Lee,Min‐Sung Kim,Jin Wook Kim,Yong Hwy Kim,Young Gyu Kim,Chul‐Kee Park
出处
期刊:Neurosurgical Focus [Journal of Neurosurgery Publishing Group]
卷期号:51 (2): E21-E21 被引量:13
标识
DOI:10.3171/2021.5.focus21184
摘要

OBJECTIVE With the advancement of 3D modeling techniques and visualization devices, augmented reality (AR)–based navigation (AR navigation) is being developed actively. The authors developed a pilot model of their newly developed inside-out tracking AR navigation system. METHODS The inside-out AR navigation technique was developed based on the visual inertial odometry (VIO) algorithm. The Quick Response (QR) marker was created and used for the image feature–detection algorithm. Inside-out AR navigation works through the steps of visualization device recognition, marker recognition, AR implementation, and registration within the running environment. A virtual 3D patient model for AR rendering and a 3D-printed patient model for validating registration accuracy were created. Inside-out tracking was used for the registration. The registration accuracy was validated by using intuitive, visualization, and quantitative methods for identifying coordinates by matching errors. Fine-tuning and opacity-adjustment functions were developed. RESULTS ARKit-based inside-out AR navigation was developed. The fiducial marker of the AR model and those of the 3D-printed patient model were correctly overlapped at all locations without errors. The tumor and anatomical structures of AR navigation and the tumors and structures placed in the intracranial space of the 3D-printed patient model precisely overlapped. The registration accuracy was quantified using coordinates, and the average moving errors of the x-axis and y-axis were 0.52 ± 0.35 and 0.05 ± 0.16 mm, respectively. The gradients from the x-axis and y-axis were 0.35° and 1.02°, respectively. Application of the fine-tuning and opacity-adjustment functions was proven by the videos. CONCLUSIONS The authors developed a novel inside-out tracking–based AR navigation system and validated its registration accuracy. This technical system could be applied in the novel navigation system for patient-specific neurosurgery.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
shineshine发布了新的文献求助20
1秒前
Michelle发布了新的文献求助10
3秒前
丘比特应助yao采纳,获得10
3秒前
4秒前
linqi完成签到 ,获得积分10
4秒前
墨扬完成签到,获得积分10
4秒前
Martin完成签到,获得积分10
6秒前
在水一方应助xinyuxxx采纳,获得10
6秒前
CC发布了新的文献求助10
6秒前
echo发布了新的文献求助10
7秒前
8秒前
李李李完成签到,获得积分10
8秒前
8秒前
十五离别后完成签到,获得积分10
8秒前
9秒前
上善若脱碳甲醛完成签到 ,获得积分10
9秒前
yibo发布了新的文献求助10
9秒前
可爱的函函应助清荔采纳,获得10
9秒前
10秒前
英姑应助瀚子采纳,获得10
10秒前
秋天的雪完成签到,获得积分10
10秒前
西瓜完成签到,获得积分10
10秒前
10秒前
桐桐应助爱听歌老1采纳,获得10
10秒前
11秒前
3am发布了新的文献求助10
11秒前
11秒前
铌123发布了新的文献求助20
11秒前
袁月辉发布了新的文献求助10
12秒前
12秒前
端庄的寄风完成签到,获得积分10
12秒前
小飞爱科研完成签到,获得积分10
12秒前
LT完成签到 ,获得积分0
12秒前
秦罗敷完成签到,获得积分20
13秒前
小易发布了新的文献求助20
14秒前
泊凉少年发布了新的文献求助10
15秒前
Rylee发布了新的文献求助10
15秒前
吴彦祖发布了新的文献求助10
15秒前
李爱国应助ddizi采纳,获得10
17秒前
高分求助中
Aerospace Standards Index - 2025 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 1000
Teaching Language in Context (Third Edition) 1000
Identifying dimensions of interest to support learning in disengaged students: the MINE project 1000
Introduction to Early Childhood Education 1000
List of 1,091 Public Pension Profiles by Region 941
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5442393
求助须知:如何正确求助?哪些是违规求助? 4552598
关于积分的说明 14237646
捐赠科研通 4473916
什么是DOI,文献DOI怎么找? 2451715
邀请新用户注册赠送积分活动 1442571
关于科研通互助平台的介绍 1418541