Multimodal image registration system for image-guided orthopaedic surgery

We present a novel multimodality image registration system for spinal surgery. The system comprises a surface-based algorithm that performs computed tomography/magnetic resonance (CT/MR) rigid registration and MR image segmentation in an iterative manner. The segmentation/registration process progressively refines the result of MR image segmentation and CT/MR registration. For MR image segmentation, we propose a method based on the double-front level set that avoids boundary leakages, prevents interference from other objects in the image, and reduces computational time by constraining the search space. In order to reduce the registration error from the misclassification of the soft tissue surrounding the bone in MR images, we propose a weighted surface-based CT/MR registration scheme. The resultant weighted surface is registered to the segmented surface of the CT image. Contours are generated from the reconstructed CT surfaces for subsequent MR image segmentation. This process iterates till convergence. The registration method achieves accuracy comparable to conventional techniques while being significantly faster. Experimental results demonstrate the advantages of the proposed approach and its application to different anatomies.     

基于ITK的医学图像配准的应用

医学图像配准是指对于一幅医学图像寻求一种空间变换,使它与另一幅医学图像上的对应点达到空间位置上的一致。一致是指人体上的同一解剖点在两张图像上有相同的空间位置。The Insight Toolk it(简称ITK)是一个具有较强功能的医学图像处理类库,主要用于医学图像的预处理、分割及配准。主要研究图像配准算法以及ITK在医学图像配准中的应用。为采用ITK实现的一个医学图像配准的实例,对医学发展提供参考。     

三维医学图像配准在图像引导放疗中的应用

为了确定病人的摆位误差,实现精确放疗,提出一种改进的Demons弹性配准算法。采用FDK算法对锥形束CT(CBCT)图像进行三维重建,利用可视化工具包 (VTK)体绘制法可视化重建结果;在分割与配准工具包 (ITK)基础上实现Demons算法,并基于对称梯度的思想,将参考图像和浮动图像的梯度场信息加入到Demons算法中,给出新的Demons形变力公式。分别使用单模态和多模态医学图像进行配准实验,结果显示改进的Demons算法与原始Demons算法相比,配准速度更快、精度更高。基于对称梯度的Demons算法更适用于图像引导放射治疗中CBCT重建图像与CT计划图像间的配准。     

基于ITK的Mattes互信息医学图像配准研究

近年来非刚性医学图像配准在临床上的需求越来越明显,而使用互信息的方法已经受到许多学者的关注。本文较为详细的介绍了医学图像分割与配准算法工具包在VS2008中的安装和使用,基于该工具包完成了2D-2DMRI脑部图像的Mat-tes互信息配准,对互信息算法及其实现做了研究,并提出了使用图像金字塔算法策略联合互信息测度进行配准的方案。实验表明,与没有使用联合策略的配准方法相比,该方案在配准鲁棒性没有受到明显影响的同时,提高了配准速度和精度。     

An invariant approach for image registration in digital subtraction angiography

In modern medicine, digital subtraction angiography is a powerful technique for the visualization of blood vessels in a sequence of X-ray images. A serious problem encountered in this technique is misregistration of images due to patient motion. The resulting artifacts which arise from the misalignment of successive images in the sequence frequently reduce the diagnostic value of the images. In this paper, a new approach to the registration of digital angiographic image sequences is proposed. It is based on local similarity detection by means of template matching according to a combined invariants-based similarity measure and on thin-plate spline image warping. This technique is fully automatic and very efficient to correct for patient motion artifacts. The proposed algorithm for this technique has been successfully applied to register several clinical data sets including coronary applications. It works perfectly well for both slow and sudden motions and is both effective and fast.     

一种快速的三维扫描数据自动配准方法

研究了两幅和多幅深度图像的自动配准问题.在配准两幅深度图像时,结合二维纹理图像配准深度图像,具体过程是:首先,从扫描数据中提取纹理图像,特别地,针对不包含纹理图像的扫描数据提出了一种根据深度图像直接生成纹理图像的方法;然后,基于SIFT(scale-invariant feature transform)特征提取纹理图像中的兴趣像素,并通过预过滤和交叉检验兴趣像素等方法从中找出匹配像素对的候选集;之后,使用RANSAC(random sample consensus)算法,根据三维几何信息的约束找出候选集中正确的匹配像素对和相对应的匹配顶点对,并根据这些匹配顶点对计算出两幅深度图像间的刚体置换矩阵;最后,使用改进的ICP(iterative closest point)算法优化这一结果.在配准多幅深度图像时,提出了一种快速构建模型图的方法,可以避免对任意两幅深度图像作配准,提高了配准速度.该方法已成功应用于多种文物的三维逼真建模.     

Band-to-band registration model for near-equatorial Earth observation satellite images with the use of automatic control point extraction

The near-equatorial orbit (NEqO) image bands have large differences in distortion, scaling, and skewing. Therefore band-to-band registration of a near-equatorial orbit image is challenging. This study thus proposes a technique to overcome the band-to-band registration of NEqO image bands. The proposed method involves the conversion of image bands into greyscale, followed by image compression and automatic control point (CP) generation through scale-invariant feature transform. CPs are used to perform registration with both first- and second-order polynomials and spline transformation to correct the misregistration between NEqO image bands. The images used in this study are from the Malaysian RazakSAT satellite. Results show accurate registration performance. Moreover, the root-mean-square errors of the first- and second-order polynomial transformations are 4 and 3 m, respectively. These values are lower than those obtained with the use of spline transformation. Verification is performed by comparing the results of both automatic and manual transformations to the use of polynomial transformation. The results confirm the effectiveness of the proposed algorithm.     

Precision range image registration using a robust surface interpenetration measure and enhanced genetic algorithms

This paper addresses the range image registration problem for views having low overlap and which may include substantial noise. The current state of the art in range image registration is best represented by the well-known iterative closest point (ICP) algorithm and numerous variations on it. Although this method is effective in many domains, it nevertheless suffers from two key limitations: it requires prealignment of the range surfaces to a reasonable starting point; and it is not robust to outliers arising either from noise or low surface overlap. This paper proposes a new approach that avoids these problems. To that end, there are two key, novel contributions in this work: a new, hybrid genetic algorithm (GA) technique, including hill climbing and parallel-migration, combined with a new, robust evaluation metric based on surface interpenetration. Up to now, interpenetration has been evaluated only qualitatively; we define the first quantitative measure for it. Because they search in a space of transformations, GA are capable of registering surfaces even when there is low overlap between them and without need for prealignment. The novel GA search algorithm we present offers much faster convergence than prior GA methods, while the new robust evaluation metric ensures more precise alignments, even in the presence of significant noise, than mean squared error or other well-known robust cost functions. The paper presents thorough experimental results to show the improvements realized by these two contributions.     

A flexible registration and evaluation engine (f.r.e.e.)

We present an image registration framework which offers effective assistance for solving current registration problems. This work was motivated by the huge amount of registration problems in clinical applications and the problem of finding adequate solutions and properly comparing them. We have therefore designed a framework that supports the establishment, evaluation and comparison of registration approaches. Flexible registration and evaluation engine (f.r.e.e.) achieves a broad basis of algorithms by utilizing the insight segmentation and registration toolkit (ITK). This basis can be extended by virtually any new approach or algorithm, which then becomes seamlessly integrated into the method set of the f.r.e.e. framework. The framework offers suitable tools for an easy integration, optimization and proper evaluation of registration approaches, as well as an efficient utilization of the results in clinical routine. The framework is currently being evaluated at the Heidelberg University Hospital, Germany. The first results were gathered with an application implemented for the Neurosurgical Department of the hospital. In these tests the framework concept, along with its specific tools, was very promising for establishing clinical applications (e.g. preoperative neurosurgical planning; registration of cardiac images) and therefore motivated further development. The ability to automatically optimize the parameterization of registration methods regarding a given test set also proved useful, allowing more concentration on scientific problems themselves and not on the laborious task of parameter tweaking. Due to implemented abstraction layers, f.r.e.e. also allows a high degree of transparency and thus good comparability of registration approaches and results.     

Using photo-consistency to register 2D optical images of the humanface to a 3D surface model

The authors propose a novel method to register two or more optical images to a 3D surface model. The potential applications of such a registration method could be in medicine for example, in image guided interventions, surveillance and identification, industrial inspection, or telemanipulation in remote or hostile environments. Registration is performed by optimizing a similarity measure with respect to the transformation parameters. We propose a novel similarity measure based on "photo-consistency." For each surface point, the similarity measure computes how consistent the corresponding optical image information in each view is with a lighting model. The relative pose of the optical images must be known. We validate the system using data from an optical-based surface reconstruction system and surfaces derived from magnetic resonance (MR) images of the human face. We test the accuracy and robustness of the system with respect to the number of video images, video image noise, errors in surface location and area, and complexity of the matched surfaces. We demonstrate the algorithm working on 10 further optical-based reconstructions of the human head and skin surfaces derived from MR images of the heads of five volunteers. Matching four optical images to a surface model produced a 3D error of between 1.45 and 1.59 mm, at a success rate of 100 percent, where the initial misregistration was up to 16 mm or degrees from the registration position     

利用ITK和VTK集成实现三维医学图像的分割

ITK是一个对图像进行分割配准处理的开源的、基于对象的软件系统.它提供几乎所有的主流医学图像分割算法,能够解决虚拟手术中三维图像分割问题.讨论了ITK中区域生长和Level set分割算法,对CT序列图像进行分割,最后通过VTK对分割数据进行三维重建.利用ITK和VTK的功能集成,对医学图像三维组织体分割,并实现分割结果的可视化.实验证明这种方法能够满足医生对局部病变区域观测的要求,实时性良好.     

Shape matching and registration by data-driven EM

In this paper, we present an efficient and robust algorithm for shape matching, registration, and detection. The task is to geometrically transform a source shape to fit a target shape. The measure of similarity is defined in terms of the amount of transformation required. The shapes are represented by sparse-point or continuous-contour representations depending on the form of the data. We formulate the problem as probabilistic inference using a generative model and the EM algorithm. But this algorithm has problems with initialization and computing the E-step. To address these problems, we define a data-driven technique (discriminative model) which makes use of shape features. This gives a hybrid algorithm which combines the generative and discriminative models. The resulting algorithm is very fast, due to the effectiveness of shape-features for solving correspondence requiring only a few iterations. We demonstrate the effectiveness of the algorithm by testing it on standard datasets, such as MPEG7, for shape matching and by applying it to a range of matching, registration, and foreground/background segmentation problems.     

A multi-resolution area-based technique for automatic multi-modal image registration

To allow remotely sensed datasets to be used for data fusion, either to gain additional insight into the scene or for change detection, reliable spatial referencing is required. With modern remote sensing systems, reliable registration can be gained by applying an orbital model for spaceborne data or through the use of global positioning (GPS) and inertial navigation (INS) systems in the case of airborne data. Whilst, individually, these datasets appear well registered when compared to a second dataset from another source (e.g., optical to LiDAR or optical to radar) the resulting images may still be several pixels out of alignment. Manual registration techniques are often slow and labour intensive and although an improvement in registration is gained, there can still be some misalignment of the datasets. This paper outlines an approach for automatic image-to-image registration where a topologically regular grid of tie points was imposed within the overlapping region of the images. To ensure topological consistency, tie points were stored within a network structure inspired from Kohonen’s self-organising networks [24]. The network was used to constrain the motion of the tie points in a manner similar to Kohonen’s original method. Using multiple resolutions, through an image pyramid, the network structure was formed at each resolution level where connections between the resolution levels allowed tie point movements to be propagated within and to all levels. Experiments were carried out using a range of manually registered multi-modal remotely sensed datasets where known linear and non-linear transformations were introduced against which our algorithm’s performance was tested. For single modality tests with no introduced transformation a mean error of 0.011 pixels was identified increasing to 3.46 pixels using multi-modal image data. Following the introduction of a series of translations a mean error of 4.98 pixels was achieve across all image pairs while a mean error of 7.12 pixels was identified for a series of non-linear transformations. Experiments using optical reflectance and height data were also conducted to compare the manually and automatically produced results where it was found the automatic results out performed the manual results. Some limitations of the network data structure were identified when dealing with very large errors but overall the algorithm produced results similar to, and in some cases an improvement over, that of a manual operator. We have also positively compared our method to methods from two other software packages: ITK and ITT ENVI.     

医学影像处理与分析开发包MITK的设计与实现

随着VTK(visualization ToolKit)和ITK(insight segmentation and registration ToolKit)两个软件开发包的成功,医学影像领域内的研究人员越来越重视本领域内的软件包的开发问题.介绍了所开发的集成化的三维医学影像处理与分析开发包MITK(medical imaging ToolKit),其目的主要是提供一个一致的框架,整合医学图像分割、配准、可视化等功能.给出了MITK的设计目标、整体框架和关键技术的实现,以及一些应用实例以展示MITK的功能.希望MITK能成为本领域内研究开发人员的另外一个可选择的开发包.     

基于二维超声- 三维 CT 配准的肾脏穿刺定位方法可行性研究

医学影像引导的经皮肾穿刺手术是经皮肾镜取石术中建立手术通道的重要手段,高质量的 实时医学图像可以提高术中穿刺精度,减少手术风险。针对自由呼吸下经皮肾穿刺靶点的导航定位问 题,该研究提出了一种基于术中二维超声-术前三维 CT 实时配准的肾脏穿刺定位方法。首先对肾脏轮 廓特征的二维超声图像和三维 CT 图像进行由粗到精的快速配准,然后通过超声探头标定,将配准融合 后的图像注册到手术空间,实现穿刺靶点的实时定位。人体腹部模型实验结果表明,超声探头标定均 方根误差为 0.998 mm,二维超声和三维 CT 数据配准误差为 0.709 mm,平均配准运算时间为 1.15 s,最 终的平均定位误差为 2.265 mm。     

The impact of misregistration on SRTM and DEM image differences

Image differences between Shuttle Radar Topography Mission (SRTM) data and other Digital Elevation Models (DEMs) are often performed for either accuracy assessment or for estimating vegetation height across the landscape. It has been widely assumed that the effect of sub-pixel misregistration between the two models on resultant image differences is negligible, yet this has not previously been tested in detail. The aim of this study was to determine the impact that various levels of misregistration have on image differences between SRTM and DEMs. First, very accurate image co-registration was performed at two study sites between higher resolution DEMs and SRTM data, and then image differences (SRTM–DEM) were performed after various levels of misregistration were systematically introduced into the SRTM data. It was found that: (1) misregistration caused an erroneous and dominant correlation between elevation difference and aspect across the landscape; (2) the direction of the misregistration defined the direction of this erroneous and systematic elevation difference; (3) for sub-pixel misregistration the error due solely to misregistration was greater than, or equal to the true difference between the two models for substantial proportions of the landscape (e.g., greater than 33% of the area for a half-pixel misregistration); and (4) the strength of the erroneous relationship with aspect was enhanced by steeper terrain. Spatial comparisons of DEMs were found to be sensitive to even sub-pixel misregistration between the two models, which resulted in a strong erroneous correlation with aspect. This misregistration induced correlation with aspect is not likely specific to SRTM data only; we expect it to be a generic relationship present in any DEM image difference analysis.     

并行混合遗传算法在深度像配准中的应用研究

实现了基于并行混合遗传算法的深度像精确配准,并比较了四种不同测度下算法的收敛速度和配准精度。根据进程数将种群划分为相应数量的子种群,每一个进程维护一个子种群的交叉、变异和选择,并通过采用环状的最优个体迁移策略和退火选择算子,实现了基于粗粒度并行混合遗传算法的深度像精确配准。此外,还比较了点对均值、中值、点面距离以及表面间平均体积四种测度下算法的性能和优劣。实验结果表明,并行计算技术的应用能够有效加速遗传算法的收敛,减少算法的运行时间。     

遥感图像配准中特征点选择的高性能算法研究及其实现

在基于特征点的遥感图像配准过程中，特征点的自动、快速提取是影响配准精度和速度的关键．采用手工选择特征点，能够保证特征点的分布，但是自动化程度低而且耗时．该文提出了一种用于解决特征点选择的高性能算法．该算法选择的特征点分布均匀，保证了配准的精度；特征点的选择过程完全自动化，并通过并行优化进一步提高了算法的效率．     

多视点距离图像的对准算法

提出一种多视点距离图像的对准算法.该算法将有拒绝的随机抽样和迭代最近点 (ICP: Iterative Closest Point)算法结合起来,采用粗、精对准时不同的评价函数,利用最小二 乘进行多视点之间运动参数的估计.为了快速进行3D点到物体表面的最近距离和最近点的 计算,采用了物体表面的八叉树样条表示.实验结果表明,该对准算法收敛速度较快,抗噪声 能力较强,并且有较高的对准精度.     

结合纹理信息的深度像匹配

利用图像的相关性在不同深度像对应的纹理图中自动选取特征点对;然后根据Hausdorff距离判断对应点对的有效性,并利用这些对应点对获得相应的深度点对,从而计算出2个深度像之间的初始位置变换关系;最后结合一种改进的带纹理的ICP算法实现深度像的精确配准.实验结果证明:该算法不仅适用于自由曲面的深度像匹配,而且适用于规则对称物体的匹配.