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
qiang完成签到,获得积分10
刚刚
长刀介错人完成签到,获得积分10
1秒前
酸甜苦辣静夜思完成签到,获得积分10
1秒前
1秒前
2秒前
ZW发布了新的文献求助10
2秒前
2秒前
铱铱的胡萝卜完成签到,获得积分10
3秒前
mm完成签到,获得积分10
3秒前
wwh完成签到,获得积分10
3秒前
吃颗电池发布了新的文献求助10
3秒前
量子星尘发布了新的文献求助10
4秒前
Li完成签到,获得积分10
4秒前
yr完成签到,获得积分10
4秒前
LYY完成签到,获得积分10
5秒前
Ch185完成签到,获得积分10
5秒前
文静的糖豆完成签到,获得积分10
5秒前
qwerty123456完成签到,获得积分10
5秒前
5秒前
凉凉盛夏发布了新的文献求助10
5秒前
ldroc完成签到,获得积分10
6秒前
俭朴的乐巧完成签到 ,获得积分10
6秒前
7秒前
8秒前
西米露完成签到,获得积分10
8秒前
JL完成签到,获得积分10
8秒前
9秒前
Mike完成签到 ,获得积分10
9秒前
csg888888完成签到,获得积分10
9秒前
盏茶轻抿完成签到,获得积分10
9秒前
张欢欢完成签到,获得积分10
10秒前
科研通AI2S应助wdh采纳,获得10
10秒前
红星路吃饼子的派大星完成签到 ,获得积分10
10秒前
10秒前
舒服的灰狼完成签到,获得积分10
11秒前
百尺竿头完成签到,获得积分10
12秒前
朝阳发布了新的文献求助30
12秒前
幸福的蓝血完成签到,获得积分10
12秒前
虫子盐完成签到,获得积分10
12秒前
12秒前
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
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
化妆品原料学 1000
小学科学课程与教学 500
Study and Interlaboratory Validation of Simultaneous LC-MS/MS Method for Food Allergens Using Model Processed Foods 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5645431
求助须知:如何正确求助?哪些是违规求助? 4768803
关于积分的说明 15028908
捐赠科研通 4804012
什么是DOI,文献DOI怎么找? 2568656
邀请新用户注册赠送积分活动 1525914
关于科研通互助平台的介绍 1485570