亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

3-D/2-D registration of CT and MR to X-ray images

基准标记 图像配准 成像体模 人工智能 方向(向量空间) 分割 刚性变换 射线照相术 核医学 磁共振成像 计算机视觉 计算机科学 金标准(测试) 光学(聚焦) 断层摄影术 医学 放射科 数学 图像(数学) 物理 几何学 光学
作者
Dejan Tomaževič,B. Likar,T. Slivnik,F. Pernuš
出处
期刊:IEEE Transactions on Medical Imaging [Institute of Electrical and Electronics Engineers]
卷期号:22 (11): 1407-1416 被引量:168
标识
DOI:10.1109/tmi.2003.819277
摘要

A crucial part of image-guided therapy is registration of preoperative and intraoperative images, by which the precise position and orientation of the patient's anatomy is determined in three dimensions. This paper presents a novel approach to register three-dimensional (3-D) computed tomography (CT) or magnetic resonance (MR) images to one or more two-dimensional (2-D) X-ray images. The registration is based solely on the information present in 2-D and 3-D images. It does not require fiducial markers, intraoperative X-ray image segmentation, or timely construction of digitally reconstructed radiographs. The originality of the approach is in using normals to bone surfaces, preoperatively defined in 3-D MR or CT data, and gradients of intraoperative X-ray images at locations defined by the X-ray source and 3-D surface points. The registration is concerned with finding the rigid transformation of a CT or MR volume, which provides the best match between surface normals and back projected gradients, considering their amplitudes and orientations. We have thoroughly validated our registration method by using MR, CT, and X-ray images of a cadaveric lumbar spine phantom for which "gold standard" registration was established by means of fiducial markers, and its accuracy assessed by target registration error. Volumes of interest, containing single vertebrae L1-L5, were registered to different pairs of X-ray images from different starting positions, chosen randomly and uniformly around the "gold standard" position. CT/X-ray (MR/X-ray) registration, which is fast, was successful in more than 91% (82% except for Ll) of trials if started from the "gold standard" translated or rotated for less than 6 mm or 17/spl deg/ (3 mm or 8.6/spl deg/), respectively. Root-mean-square target registration errors were below 0.5 mm for the CT to X-ray registration and below 1.4 mm for MR to X-ray registration.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
二舅司机发布了新的文献求助10
3秒前
完美世界应助科研通管家采纳,获得10
5秒前
张欢馨应助科研通管家采纳,获得30
5秒前
5秒前
Wingkay完成签到 ,获得积分10
13秒前
清秀面包发布了新的文献求助10
14秒前
25秒前
大模型应助秋下采纳,获得10
29秒前
飞龙发布了新的文献求助10
35秒前
赘婿应助argon采纳,获得10
40秒前
科研通AI6.2应助清秀面包采纳,获得10
40秒前
bkagyin应助西瓜番茄采纳,获得10
41秒前
可爱的函函应助飞龙采纳,获得10
47秒前
飞龙完成签到,获得积分10
56秒前
1分钟前
1分钟前
Nian发布了新的文献求助10
1分钟前
颜九发布了新的文献求助10
1分钟前
LJC完成签到,获得积分10
1分钟前
科研通AI6.3应助俞俊敏采纳,获得10
1分钟前
1分钟前
颜九完成签到,获得积分10
1分钟前
俞俊敏发布了新的文献求助10
1分钟前
科研通AI6.2应助Nian采纳,获得10
1分钟前
orixero应助缥缈采纳,获得10
1分钟前
2分钟前
CodeCraft应助科研通管家采纳,获得10
2分钟前
SciGPT应助科研通管家采纳,获得10
2分钟前
张欢馨应助科研通管家采纳,获得10
2分钟前
大头完成签到 ,获得积分10
2分钟前
2分钟前
跳跃雨寒完成签到 ,获得积分10
2分钟前
2分钟前
123123完成签到 ,获得积分10
2分钟前
鹏虫虫完成签到 ,获得积分10
2分钟前
123完成签到 ,获得积分10
2分钟前
秋下完成签到,获得积分10
3分钟前
凶狠的映易完成签到 ,获得积分10
3分钟前
3分钟前
Nian发布了新的文献求助10
3分钟前
高分求助中
(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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Scientific Writing and Communication: Papers, Proposals, and Presentations 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6371605
求助须知:如何正确求助?哪些是违规求助? 8185245
关于积分的说明 17271304
捐赠科研通 5426013
什么是DOI,文献DOI怎么找? 2870525
邀请新用户注册赠送积分活动 1847432
关于科研通互助平台的介绍 1694042