基于节点拓扑一致性的2D/3D冠脉血管非刚性配准

目前,冠状动脉介入手术主要采用传统冠脉成像CCA加冠脉CT成像CCTA辅助的方式.但是,CCTA下的3D图像获取的是某一时刻的静态图像,在心跳和呼吸作用下,CCA下动态2D图像和CCTA下静态3D图像的血管可能并不处于同一位置,彼此之间会具有很大的形态及位置差异.本文在2D和3D中心线基础上,利用血管曲线特征对2种维度的血管进行粗糙和精细两级配准操作.在粗糙配准中,通过考虑节点间的拓扑关系一致性取消以往算法的双向一对一的对齐约束,对血管间的分支点进行多对多对齐配准.在精细配准中,基于节点对齐的配对血管段间采用伸缩特性的DTW技术进行像素间配准.实验结果表明研究提出的方法具有良好的效果.     

Nonrigid 2-D/3-D registration for patient specific bronchoscopy simulation with statistical shape modeling: phantom validation

This paper presents a nonrigid registration two-dimensional/three-dimensional (2-D/3-D) framework and its phantom validation for subject-specific bronchoscope simulation. The method exploits the recent development of five degrees-of-freedom miniaturized catheter tip electromagnetic trackers such that the position and orientation of the bronchoscope can be accurately determined. This allows the effective recovery of unknown camera rotation and airway deformation, which is modelled by an active shape model (ASM). ASM captures the intrinsic variability of the tracheo-bronchial tree during breathing and it is specific to the class of motion it represents. The method reduces the number of parameters that control the deformation, and thus greatly simplifies the optimisation procedure. Subsequently, pq-based registration is performed to recover both the camera pose and parameters of the ASM. Detailed assessment of the algorithm is performed on a deformable airway phantom, with the ground truth data being provided by an additional six degrees-of-freedom electromagnetic (EM) tracker to monitor the level of simulated respiratory motion.     

Voxel-based 2-D/3-D registration of fluoroscopy images and CT scansfor image-guided surgery

Registration of intraoperative fluoroscopy images with preoperative 3D CT images can he used for several purposes in image-guided surgery. On the one hand, it can be used to display the position of surgical instruments, which are being tracked by a localizer, in the preoperative CT scan. On the other hand, the registration result can be used to project preoperative planning information or important anatomical structures visible in the CT image on to the fluoroscopy image. For this registration task, a novel voxel-based method in combination with a new similarity measure (pattern intensity) has been developed. The basic concept of the method is explained at the example of 2D/3D registration of a vertebra in an X-ray fluoroscopy image with a 3D CT image. The registration method is described, and the results for a spine phantom are presented and discussed. Registration has been carried out repeatedly with different starting estimates to study the capture range. Information about registration accuracy has been obtained by comparing the registration results with a highly accurate “ground-truth” registration, which has been derived from fiducial markers attached to the phantom prior to imaging. In addition, registration results for different vertebrae have been compared. The results show that the rotation parameters and the shifts parallel to the projection plane can accurately be determined from a single projection. Because of the projection geometry, the accuracy of the height above the projection plane is significantly lower     

Improvement of depth position in 2-D/3-D registration of knee implants using single-plane fluoroscopy

Two-dimensional (2-D)/three-dimensional (3-D) registration techniques using single-plane fluoroscopy are highly important for analyzing 3-D kinematics in applications such as total knee arthroplasty (TKA) implants. The accuracy of single-plane fluoroscopy-based techniques in the determination of translation perpendicular to the image plane (depth position), however, is relatively poor because a change in the depth position causes only small changes in the 2-D silhouette. Accuracies achieved in depth position using conventional 2-D/3-D registration techniques are insufficient for clinical applications. Therefore, we propose a technique for improving the accuracy of depth position determination in order to develop a system for analyzing knee kinematics over the full six degrees of freedom (6 DOF) using single-plane fluoroscopy. In preliminary experiments, the behaviors of errors for each free variable were quantified as evaluation curves by examining changes in cost function with variations in the free variable. The evaluation curve for depth position was more jagged, and the curve peak less pointy, compared to the evaluation curves of the other five variables, and the curve was found to behave differently. Depth position is therefore optimized independently of the other variables, using an approximate evaluation curve of depth position prepared after initial registration. Accuracy of the proposed technique was evaluated by computer simulation and in vitro tests, with validation of absolute position and orientation performed for each knee component. In computer simulation tests, root-mean-square error (RMSE) in depth position was improved from 2.6 mm (conventional) to 0.9 mm (proposed), whereas for in vitro tests, RMSE improved from 3.2 mm to 1.4 mm. Accuracy of the estimation of the remaining two translational and three rotational variables was found to be almost the same as that obtained by conventional techniques. Results of in vivo tests are also described in which the possibility of full 6 DOF kinematic analysis of TKA implants is shown.     

A robust method for registration of three-dimensional knee implant models to two-dimensional fluoroscopy images

A method was developed for registering three-dimensional knee implant models to single plane X-ray fluoroscopy images. We use a direct image-to-image similarity measure, taking advantage of the speed of modern computer graphics workstations to quickly render simulated (predicted) images. As a result, the method does not require an accurate segmentation of the implant silhouette in the image (which can be prone to errors). A robust optimization algorithm (simulated annealing) is used that can escape local minima and find the global minimum (true solution). Although we focus on the analysis of total knee arthroplasty (TKA) in this paper, the method can be (and has been) applied to other implanted joints, including, but not limited to, hips, ankles, and temporomandibular joints. Convergence tests on an in vivo image show that the registration method can reliably find poses that are very close to the optimal (i.e., within 0.4 degrees and 0.1 mm), even from starting poses with large initial errors. However, the precision of translation measurement in the Z (out-of-plane) direction is not as good. We also show that the method is robust with respect to image noise and occlusions. However, a small amount of user supervision and intervention is necessary to detect cases when the optimization algorithm falls into a local minimum. Intervention is required less than 5% of the time when the initial starting pose is reasonably close to the correct answer, but up to 50% of the time when the initial starting pose is far away. Finally, extensive evaluations were performed on cadaver images to determine accuracy of relative pose measurement. Comparing against data derived from an optical sensor as a "gold standard," the overall root-mean-square error of the registration method was approximately 1.5 degrees and 0.65 mm (although Z translation error was higher). However, uncertainty in the optical sensor data may account for a large part of the observed error.     

Intraoperative image-based multiview 2D/3D registration for image-guided orthopaedic surgery: incorporation of fiducial-based C-arm tracking and GPU-acceleration

Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines.     

图像导引介入治疗中可视化3D的2D/3D图像数据分析

三维成像对许多医学过程(根本上是对患者的健康)来说,是非常关键的。本文探讨了三维成像方法的与众不同之处,以及作为一种不断发展创新的技术,临床医生们对它的需求和期待。     

高分辨雷达/红外成像复合系统的空间配准方法

为实现高分辨雷达/红外成像复合制导系统的空间配准,首先提出了一种基于无偏转换测量的精确极大似然坐标变换法来完成由球坐标系到笛卡尔坐标系的坐标转换,然后提出了一种通过标定雷达和红外相机实现空间配准的方法.为提高空间配准的精度,用提出的坐标变换法估计目标在笛卡尔坐标系下的真实位置,在红外图像处理中提出了一种多灰度细分质心算...     

Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration

Generation of digitally reconstructed radiographs (DRRs) is computationally expensive and is typically the rate-limiting step in the execution time of intensity-based two-dimensional to three-dimensional (2D-3D) registration algorithms. We address this computational issue by extending the technique of light field rendering from the computer graphics community. The extension of light fields, which we call attenuation fields (AFs), allows most of the DRR computation to be performed in a preprocessing step; after this precomputation step, DRRs can be generated substantially faster than with conventional ray casting. We derive expressions for the physical sizes of the two planes of an AF necessary to generate DRRs for a given X-ray camera geometry and all possible object motion within a specified range. Because an AF is a ray-based data structure, it is substantially more memory efficient than a huge table of precomputed DRRs because it eliminates the redundancy of replicated rays. Nonetheless, an AF can require substantial memory, which we address by compressing it using vector quantization. We compare DRRs generated using AFs (AF-DRRs) to those generated using ray casting (RC-DRRs) for a typical C-arm geometry and computed tomography images of several anatomic regions. They are quantitatively very similar: the median peak signal-to-noise ratio of AF-DRRs versus RC-DRRs is greater than 43 dB in all cases. We perform intensity-based 2D-3D registration using AF-DRRs and RC-DRRs and evaluate registration accuracy using gold-standard clinical spine image data from four patients. The registration accuracy and robustness of the two methods is virtually identical whereas the execution speed using AF-DRRs is an order of magnitude faster.     

2D and 3D imaging of small animals and the human radial artery with a high resolution detector for PET

The performance of a pair of multicrystal, high-resolution, bismuth germanate (BGO) block detectors for positron emission tomography (PET) has been investigated. Utilizing the detectors at a separation of 100 mm, the spatial resolutions and count rate response of the block have been measured. These measurements indicate maximum spatial resolutions of 3.6 and 4.5 mm (FWHM) in the two axes of the block and a maximum coincidence rate of 3400 cps. The system has been used to observe the regional kinetics of positron-emitting radionuclides in the rat brain and the human radial artery. Designs for a small diameter, no-septa tomograph incorporating these detectors have been considered. Simulations demonstrate the possibilities of following tracer uptake within the rat brain and radial artery. Three-dimensional tomographic data-sets of a 20-mm uniform cylinder, obtained from rotating the two blocks, indicate good uniformity in the field of view (FOV) of 25 mm.     

Gradient-based 2-D/3-D rigid registration of fluoroscopic X-ray to CT

We present a gradient-based method for rigid registration of a patient preoperative computed tomography (CT) to its intraoperative situation with a few fluoroscopic X-ray images obtained with a tracked C-arm. The method is noninvasive, anatomy-based, requires simple user interaction, and includes validation. It is generic and easily customizable for a variety of routine clinical uses in orthopaedic surgery. Gradient-based registration consists of three steps: 1) initial pose estimation; 2) coarse geometry-based registration on bone contours, and; 3) fine gradient projection registration (GPR) on edge pixels. It optimizes speed, accuracy, and robustness. Its novelty resides in using volume gradients to eliminate outliers and foreign objects in the fluoroscopic X-ray images, in speeding up computation, and in achieving higher accuracy. It overcomes the drawbacks of intensity-based methods, which are slow and have a limited convergence range, and of geometry-based methods, which depend on the image segmentation quality. Our simulated, in vitro, and cadaver experiments on a human pelvis CT, dry vertebra, dry femur, fresh lamb hip, and human pelvis under realistic conditions show a mean 0.5-1.7 mm (0.5-2.6 mm maximum) target registration accuracy.     

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

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 L1) of trials if started from the "gold standard" translated or rotated for less than 6 mm or 17 degrees (3 mm or 8.6 degrees), 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.     

浅谈向Google Earth发布3D模型的方法

Google Earth软件是目前对3D建模技术支持较好的软件.城市景观3D建模技术在城市规划、突发事件应急等许多领域都有重要的应用.分析了向Google Earth发布3D模型的技术并就其中的难点问题进行了分析并提出了解决方法.对城市景观3D建模项目的开发具有一定的指导意义.     

Multiple-object 2-D-3-D registration for noninvasive pose identification of fracture fragments

This paper presents a multiple-object 2-D-3-D registration technique for noninvasively identifying the poses of fracture fragments in the space of a preoperative treatment plan. The plan is made by manipulating and aligning computer models of individual fracture fragments that are segmented from a diagnostic computed tomography. The registration technique iteratively updates the treatment plan and matches its digitally reconstructed radiographs to a small number of intraoperative fluoroscopic images. The proposed approach combines an image similarity metric that integrates edge information with mutual information, and a global-local optimization scheme, to deal with challenges associated with the registration of multiple small fragments and limited imaging orientations in the operating room. The method is easy to use as minimum user interaction is required. Experiments on simulated fractures and two distal radius fracture phantoms demonstrate clinically acceptable target registration errors with capture range as large as 10 mm.     

A comparison of similarity measures for use in 2-D-3-D medicalimage registration

A comparison of six similarity measures for use in intensity-based two-dimensional-three-dimensional (2-D-3-D) image registration is presented. The accuracy of the similarity measures are compared to a “gold-standard” registration which has been accurately calculated using fiducial markers. The similarity measures are used to register a computed tomography (CT) scan of a spine phantom to a fluoroscopy image of the phantom. The registration is carried out within a region-of-interest in the fluoroscopy image which is user defined to contain a single vertebra. Many of the problems involved in this type of registration are caused by features which were not modeled by a phantom image alone. More realistic “gold-standard” data sets were simulated using the phantom image with clinical image features overlaid. Results show that the introduction of soft-tissue structures and interventional instruments into the phantom image can have a large effect on the performance of some similarity measures previously applied to 2-D-3-D image registration. Two measures were able to register accurately and robustly even when soft-tissue structures and interventional instruments were present as differences between the images. These measures were pattern intensity and gradient difference. Their registration accuracy, for all the rigid-body parameters except for the source to film translation, was within a root-mean-square (rms) error of 0.53 mm or degrees to the “gold-standard” values. No failures occurred while registering using these measures     

Recursive pruning of the 2D DFT with 3D signal processingapplications

A recursively pruned radix-(2×2) two-dimensional (2D) fast Fourier transform (FFT) algorithm is proposed to reduce the number of operations involved in the calculation of the 2D discrete Fourier transform (DFT). It is able to compute input and output data points having multiple and possibly irregularly shaped (nonsquare) regions of support. The computational performance of the recursively pruned radix-(2×2) 2D FFT algorithm is compared with that of pruning algorithms based on the one-dimensional (1D) FFT. The former is shown to yield significant computational savings when employed in the combined 2D DFT/1D linear difference equation filter method to enhance three-dimensional spatially planar image sequences, and when employed in the MixeD moving object detection and trajectory estimation algorithm