Computer-Assisted Preoperative Planning for Reduction of Proximal Femoral Fracture Using 3-D-CT Data

This paper describes procedures for repositioning calculations of fractured bone fragments using 3-D-computed tomography (CT), aimed at preoperative planning for computer-guided fracture reduction of the proximal femur. Fracture boundaries of the bone fragments, as ldquofracture lines (FLs),rdquo and the mirror-transformed contralateral femur shape extracted from 3-D-CT were used for repositioning of the fragments. We first describe a method for extracting FLs based on 3-D curvature analysis and then formulate repositioning methods based on registration of bone fragments using the following three constraints: 1) contralateral (CL) femur shape; 2) FLs; and 3) both CL femur shape and fracture lines, as ldquoboth constraintsrdquo. We performed experiments using CT datasets from five simulated and four real patients with proximal femoral fracture. We evaluated the rotation error in reposition calculations and the contact ratio between repositioned fragment boundaries, which are crucial for the recovery of proper functional axes and bone adhesion of fragments, respectively. Experimental results showed that good accuracy and stability were attainable when registration using both constraints was performed after registration using the fracture-line constraint. On average, 6.0deg plusmn0.8deg in rotation error and 89% plusmn 3% in contact ratio were obtained without providing precise initial values.     

Image registration for image-based rendering.

Image-based rendering (IBR) has received much attention in recent years for its ability to synthesize photo-realistic novel views. To support translational motion, existing IBR methods either require a large amount of reference images or assume that some geometric information is available. However, rendering with a large amount of images is very expensive in terms of image acquisition, data storage, and memory costs. As IBR accepts various kinds of geometric proxy, we may use image registration techniques, such as stereo matching and structure and motion recognition, to obtain geometric information to help reduce the number of images required. Unfortunately, existing image registration techniques only support a small search range and require closely sampled reference images. This results in a high spatial sampling rate, making IBR impractical for use in scalable walkthrough environments.Our primary objective of this project is to develop an image registration technique that would recover the geometric proxy for IBR while, at the same time, reducing the number of reference images required. In this paper, we analyze the roles and requirements of an image registration technique for reducing the spatial sampling rate. Based on these requirements, we present a novel image registration technique to automatically recover the geometric proxy from reference images. With the distinguishing feature of supporting a large search range, the new method can accurately identify correspondences even though the reference images may only be sparsely sampled. This can significantly reduce the acquisition effort, the model size, and the memory cost.     

Spherical harmonics based intrasubject 3-D kidney modeling/registration technique applied on partial information

This paper presents a three-dimensional (3-D) shape reconstruction/intrapatient rigid registration technique used to establish a Nephron-Sparing Surgery preoperative planning. The usual preoperative imaging system is the Spiral CT Urography, which provides successive 3-D acquisitions of complementary information on kidney anatomy. Because the kidney is difficult to demarcate from the liver or from the spleen only limited information on its volume or surface is available. In this paper, we propose a methodology allowing a global kidney spatial representation on a spherical harmonics basis. The spherical harmonics are exploited to recover the kidney 3-D shape and also to perform intrapatient 3-D rigid registration. An evaluation performed on synthetic data showed that this technique presented lower performance then expected for the 3-D shape recovering but exhibited registration results slightly more accurate as the iterative closest point technique with faster computation time.     

蚁群算法和Powell法结合的多分辨率三维图像配准

基于互信息的配准方法具有精度高,鲁棒性强的特点,成为近年来图像配准研究的热点.但基于互信息的目标函数存在许多局部极值,为配准的优化过程带来了很大的困难.该文提出了一种蚁群算法和Powell法相结合的多分辨率搜索优化算法.该算法以互信息作为相似性测度,采用基于小波变换的多分辨率策略,将蚁群算法与Powell法结合起来对三维的CT,MR图像进行了配准.实验结果表明,这种方法能够有效地克服互信息函数的局部极值,大大地提高了配准精度,达到亚像素级.     

An ultrasonic approach to localization of fiducial markers forinteractive, image-guided neurosurgery. I. Principles

Fiducial markers are reference points used in the registration of image space(s) with physical (patient) space. As applied to interactive, image-guided surgery, the registration of image space with physical space allows the current location of a surgical tool to be indicated on a computer display of patient-specific preoperative images. This intrasurgical guidance information is particularly valuable in surgery within the brain, where visual feedback is limited. The accuracy of the mapping between physical and image space depends upon the accuracy with which the fiducial markers were located in each coordinate system. To effect accurate space registration for interactive, image-guided neurosurgery, the use of permanent fiducial markers implanted into the surface of the skull is proposed in this paper. These small cylindrical markers are composed of materials that make them visible in the image sets. The challenge lies in locating the subcutaneous markers in physical space. This paper presents an ultrasonic technique for transcutaneously detecting the location of these markers. The technique incorporates an algorithm based on detection of characteristic properties of the reflected A-mode ultrasonic waveform. The results demonstrate that ultrasound is an appropriate technique for accurate transcutaneous marker localization. The companion paper to this article describes an automatic, enhanced implementation of the marker-localization theory described in this article     

基于SURF的图像配准方法研究

图像配准在计算机视觉、医学诊断与治疗、图像拼接等领域有广泛的应用.基于特征的方法具有压缩信息量、执行速度快、精度高等优点,成为近年来研究的热点,SIFT是其中之一.但传统的SIFT方法数据量大、计算耗时长,提出了一种基于SURF的图像配准方法.首先用SURF方法提取特征点,其次用最近邻匹配法找出对应匹配点对,结合RANSAC和最小二乘法求出图像之间的映射关系,最后利用所求的变换参数插值得到配准后的图像.实验表明:该配准算法既满足参数估算准确的要求,又具有比SIFT计算量小、速度快的优点,有一定的理论和应用价值.     

Likelihood maximization approach to image registration

A likelihood maximization approach to image registration is developed in this paper. It is assumed that the voxel values in two images in registration are probabilistically related. The principle of maximum likelihood is then exploited to find the optimal registration: the likelihood that given image f, one has image g and given image g, one has image f is optimized with respect to registration parameters. All voxel pairs in the overlapping volume or a portion of it can be used to compute the likelihood. A knowledge-based method and a self-consistent technique are proposed to obtain the probability relation. In the knowledge-based method, prior knowledge of the distribution of voxel pairs in two registered images is assumed, while such knowledge is not required in the self-consistent method. The accuracy and robustness of the likelihood maximization approach is validated by single modality registration of single photon emission computed tomographic (SPECT) images and magnetic resonance (MR) images and by multimodality registration (MR/SPECT). The results demonstrate that the performance of the likelihood maximization approach is comparable to that of the mutual information maximization technique. Finally the relationship between the likelihood approach and the entropy, conditional entropy, and mutual information approaches is discussed.     

一种实用的小目标配准方法

图像配准是图像融合技术的基本环节和首要问题,只有经过配准后的图像才能进行有效的融合。其中,小目标由于几乎无特征信息可以利用,所以常规的配准方法都不适用。针对图像识别中小目标的配准问题,分析了其配准特点,创新性地提出了先配准目标视场,再配准目标位置的方法,提出了视场配准的概念。首先运用成像原理,用焦距、分辨率和像元尺寸建立不同CCD之间的视场对应关系,利用此关系完成目标视场的截取放大,使不同CCD得到的图像视场一样大。然后在分析通常采用的最小平均绝对误差（MAD）相关匹配方法缺陷的基础上,提出用最多近邻点距离（MCD）的匹配方法来对准目标位置,完成目标质心的配准。实验结果表明,此方法可以很好地配准小目标,且误差不超过2个像素。由于其针对性强．因而具有较强的实际应用价值。     

Alignment of sparse freehand 3-D ultrasound with preoperative images of the liver using models of respiratory motion and deformation

We present a method for alignment of an interventional plan to optically tracked two-dimensional intraoperative ultrasound (US) images of the liver. Our clinical motivation is to enable the accurate transfer of information from three-dimensional preoperative imaging modalities [magnetic resonance (MR) or computed tomography (CT)] to intraoperative US to aid needle placement for thermal ablation of liver metastases. An initial rigid registration to intraoperative coordinates is obtained using a set of US images acquired at maximum exhalation. A preprocessing step is applied to both the preoperative images and the US images to produce evidence of corresponding structures. This yields two sets of images representing classification of regions as vessels. The registration then proceeds using these images. The preoperative images and plan are then warped to correspond to a single US slice acquired at an unknown point in the breathing cycle where the liver is likely to have moved and deformed relative to the preoperative image. Alignment is constrained using a patient-specific model of breathing motion and deformation. Target registration error is estimated by carrying out simulation experiments using resliced MR volumes to simulate real US and comparing the registration results to a "bronze-standard" registration performed on the full MR volume. Finally, the system is tested using real US and verified using visual inspection.     

保留股骨距的骨水泥型双动半髋人工关节置换治疗高龄转子间骨折

目的：探讨高龄转子间骨折行双动人工关节置换的手术适应症及手术方法。方法：对16例老年转子间骨折采取人工双动半髋关节置换术,男9例,女7例,年龄67-91岁,平均76．5岁。骨折分类按Evans分型,EvansⅠ型12例,EvansⅡ型4例,手术过程中保留股骨距,大转子行改良张力带钢丝固定后,行分次骨水泥双动人工关节置换。结果：手术时间最短52分钟-72分钟,平均68分钟;术中出血210ml-400ml,平均326ml;术后6月手术疗效评价按Harris评分,76分-93分,平均78．5分,无严重并发症发生。术后随访6～22个月,平均18．4月,随访期间未见假体松动及髋臼磨损。结论：以双动人工关节置换治疗高龄转子间骨折是一种较为有效、可行的方法;合适的手术适应症选择及正确的假体选择和手术操作是其关键。     

基于简单Schur凹函数的图像配准测度研究

 使用互信息或归一化互信息进行图像配准时,由于噪声、模态、插值等影响,测度函数存在许多局部极值,收敛范围较窄,有可能导致误配准.该文根据一个简单的Schur凹函数,充分利用它的特殊上凸性来消除噪声等引起的小概率分布,并由Jensen-Schur测度、广义距离测度和 f 信息测度的定义,构造了六种新测度.从运算时间、收敛性能、抗噪鲁棒性方面,对这六种测度、互信息和归一化互信息进行了比较和分析.实验结果表明,Jensen-Schur-beta和D-beta测度的收敛性能优于其它测度,抗噪声能力强于其它测度,运算速度快于互信息和归一化互信息.     

Registration of stereo and temporal images of the retina

The registration of retinal images is required to facilitate the study of the optic nerve head and the retina. The method we propose combines the use of mutual information as the similarity measure and simulated annealing as the search technique. It is robust toward large transformations between the images and significant changes in light intensity. By using a pyramid sampling approach combined with simulated reannealing we find that registration can be achieved to predetermined precision, subject to choice of interpolation and the constraint of time. The algorithm was tested on 49 pairs of stereo images and 48 pairs of temporal images with success.     

An image registration algorithm based on phase correlation and the classical Lucas–Kanade technique

Image registration is defined as an important process in image processing in order to align two or more images. A new image registration algorithm for translated and rotated pairs of 2D images is presented in order to achieve subpixel accuracy and spend a small fraction of computation time. To achieve the accurate rotation estimation, we propose a two-step method. The first step uses the Fourier Mellin Transform and phase correlation technique to get the large rotation, then the second one uses the Fourier Mellin Transform combined with an enhance Lucas–Kanade technique to estimate the accurate rotation. For the subpixel translation estimation, the proposed algorithm suggests an improved Hanning window as a preprocessing task to reduce the noise in images then achieves a subpixel registration in two steps. The first step uses the spatial domain approach which consists of locating the peak of the cross-correlation surface, while the second uses the frequency domain approach, based on low-frequency (aliasing-free part) of aliased images. Experimental results presented in this work show that the proposed algorithm reduces the computational complexities with a better accuracy compared to other subpixel registration algorithms.     

Semiautomatic 3-D image registration as applied to interventional MRI liver cancer treatment

We evaluated semiautomatic, voxel-based registration methods for a new application, the assessment and optimization of interventional magnetic resonance imaging (I-MRI) guided thermal ablation of liver cancer. The abdominal images acquired on a low-field-strength, open I-MRI system contain noise, motion artifacts, and tissue deformation. Dissimilar images can be obtained as a result of different MRI acquisition techniques and/or changes induced by treatments. These features challenge a registration algorithm. We evaluated one manual and four automated methods on clinical images acquired before treatment, immediately following treatment, and during several follow-up studies. Images were T2-weighted, T1-weighted Gd-DTPA enhanced, T1-weighted, and short-inversion-time inversion recovery (STIR). Registration accuracy was estimated from distances between anatomical landmarks. Mutual information gave better results than entropy, correlation, and variance of gray-scale ratio. Preprocessing steps such as masking and an initialization method that used two-dimensional (2-D) registration to obtain initial transformation estimates were crucial. With proper preprocessing, automatic registration was successful with all image pairs having reasonable image quality. A registration accuracy of approximately equal to 3 mm was achieved with both manual and mutual information methods. Despite motion and deformation in the liver, mutual information registration is sufficiently accurate and robust for useful applications in I-MRI thermal ablation therapy.     

Multimodality Image Registration Using Spatial Procrustes Analysis and Modified Conditional Entropy

In this paper, we propose a new image registration technique using two kinds of information known as object shapes and voxel intensities. The proposed approach consists of two registration steps. First, an initial registration is carried out for two volume images by applying Procrustes analysis theory to the two sets of 3D feature points representing object shapes. During this first stage, a volume image is segmented by using a geometric deformable model. Then, 3D feature points are extracted from the boundary of a segmented object. We conduct an initial registration by applying Procrustes analysis theory with two sets of 3D feature points. Second, a fine registration is followed by using a new measure based on the entropy of conditional probabilities. Here, to achieve the final registration, we define a modified conditional entropy (MCE) computed from the joint histograms for voxel intensities of two given volume images. By using a two step registration method, we can improve the registration precision. To evaluate the performance of the proposed registration method, we conduct various experiments for our method as well as existing methods based on the mutual information (MI) and maximum likelihood (ML) criteria. We evaluate the precision of MI, ML and MCE-based measurements by comparing their registration traces obtained from magnetic resonance (MR) images and transformed computed tomography (CT) images with respect to x-translation and rotation. The experimental results show that our method has great potential for the registration of a variety of medical images.     

Assessment of operation plan performance under uncertainty

A military air operations plan contains a number of sequential and/or parallel tasks. Given information about the battlefield situation (including a task status estimate) during the plan's execution, it is necessary to assess the situation impact on the plan, especially whether the entire plan would be delayed. Plan performance assessment fuses the task status estimate into the status estimate of the entire plan. The plan performance assessment assists the air operations commander in deciding the need for plan modification to assure the air operations goal. The performance assessment of the plan must deal with uncertainty in the task status estimate. This paper presents a comparative study of two information fusion techniques that infer the entire plan's status estimate from the task status estimate under uncertainty: a decomposition technique with low computational cost and a composition technique with high computational cost. The test results of these two techniques indicate their similar estimation accuracies. Due to its low computational cost, the decomposition technique is recommended. Guidelines for applying the decomposition technique to a large-scale complex task plan are also provided     

Non-Iterative Hierarchical Registration for Medical Images

Digital images from diverse medical imaging modalities and from different imaging times are becoming an indispensable information resource for making clinical decisions. Image registration is an enabling technique for more fully utilizing the embedded heterogeneous image information. However, in addition to the complex differences and deformations inherent in the medical images, the increasing scope, resolution, and dimensionality of imaging pose significant challenges in this medical arena. Wavelets have shown great potential in multi-scale registration due to their superior capacity for representing image information at different resolutions and spatial frequencies. However, the application of wavelets in registration is hindered by their lack of rotation- and translation-invariance. To overcome this obstacle, this paper proposes a non-iterative hierarchical registration method based on points of interest which are extracted automatically from wavelet decompositions. The proposed algorithm for two-dimensional monomodal medical images has been validated by experiments on phantom data and clinical imaging data. This proposed non-iterative method provides a computationally efficient registration, as well as assists in avoiding the non-convergence problem.     

Fluoroscopic bone fragment tracking for surgical navigation in femur fracture reduction by incorporating optical tracking of hip joint rotation center

A new method for fluoroscopic tracking of a proximal bone fragment in femoral fracture reduction is presented. The proposed method combines 2-D and 3-D image registration from single-view fluoroscopy with tracking of the head center position of the proximal femoral fragment to improve the accuracy of fluoroscopic registration without the need for repeated manual adjustment of the C-arm as required in stereo-view registrations. Kinematic knowledge of the hip joint, which has a positional correspondence with the femoral head center and the pelvis acetabular center, allows the position of the femoral fragment to be determined from pelvis tracking. The stability of the proposed method with respect to fluoroscopic image noise and the desired continuity of the fracture reduction operation is demonstrated, and the accuracy of tracking is shown to be superior to that achievable by single-view image registration, particularly in depth translation.     

A VLSI Architecture for Image Registration in Real Time

Image registration is an ubiquitous task occurring in countless image analysis applications. A dedicated implementation of image registration algorithms is the best approach to meet the intensive computation requirements of implementing image registration schemes in real time. This paper presents an efficient VLSI architecture for real-time implementation of image registration algorithms using an exhaustive search method. Normalized cross correlation function, mean square error, and blue screen technique algorithms are implemented for image registration. The architecture is based on a data flow design that allows sequential inputs but performs parallel processing. Based on the architecture, a programmable chip can be designed for image registration. Chips can be cascaded to achieve better performance and sizes of both the search and the reference image which can vary with time from a small to a very large value.     

对数极坐标变换域下互信息图像配准方法

当待配准中的图像中存在较大的尺度变换时,传统的图像互信息配准方法对图像尺度变换参数很敏感,易于在优化搜索时陷入局部极值点,配准效果不好。文中提出基于对数极坐标（log—polar）域的图像配准方法,它较好地分离了图像缩放参数和图像旋转参数的相互影响。仿真结果表明,该方法在大尺度图像配准场合应用时比通常的互信息方法有更高的精度和鲁棒性。