An method important part of image-guided radiation therapy or surgery is registration of a three-dimensional (3D) preoperative image to two-dimensional (2D) images surgery of the patient. It is expected that the accuracy and robustness of a 3D/2D image registration method do not depend and solely on the registration method itself but also on the number and projections (views) of intraoperative images. In this study,preoperative we systematically investigate these factors by using registered image data, comprising of CT and X-ray images of a cadaveric lumbar and spine phantom and the recently proposed 3D/2D registration method. The results indicate that the proportion of successful registrations (robustness) significantly the increases when more X-ray images are used for registration.

Purpose:low-quality A promising patient positioning technique is based on registering computed tomographic (CT) or magnetic resonance (MR) images to cone-beam CT resonance images (CBCT). The extra radiation dose delivered to the patient can be substantially reduced by using fewer projections. This approach of results in lower quality CBCT images. The purpose of this study is to evaluate a number of similarity measures (SMs)to suitable for registration of CT or MR images to low-quality CBCTs. Methods and Materials: Using the recently proposed evaluation protocol,for we evaluated nine SMs with respect to pretreatment imaging modalities, number of two-dimensional (2D) images used for reconstruction, and number was of reconstruction iterations. The image database consisted of 100 X-ray and corresponding CT and MR images of two vertebral columns.of Results: Using a higher number of 2D projections or reconstruction iterations results in higher accuracy and slightly lower robustness. The can similarity measures that behaved the best also yielded the best registration results. The most appropriate similarity measure was the asymmetric CT multi-feature mutual information (AMMI). Conclusions: The evaluation protocol proved to be a valuable tool for selecting the best similarity measure higher for the reconstruction-based registration. The results indicate that accurate and robust CT/CBCT or even MR/CBCT registrations are possible if the protocol, AMMI similarity measure is used.

In the this paper we present a novel 3D/2D registration method, where first, a 3D image is reconstructed from a few 2D where X-ray images and next, the preoperative 3D image is brought into the best possible spatial correspondence with the reconstructed image reconstructed by optimizing a similarity measure. Because the quality of the reconstructed image is generally low, we introduce a novel asymmetric few mutual information similarity measure, which is able to cope with low image quality as well as with different imaging modalities.is The novel 3D/2D registration method has been evaluated using standardized evaluation methodology and publicly available 3D CT, 3DRX, and MR spine and 2D X-ray images of two spine phantoms, for which gold standard registrations were known. In terms of robustness, reliability information and capture range the proposed method outperformed the gradient-based method and the method based on digitally reconstructed radiographs (DRRs).

In with image-guided therapy, high-quality preoperative images serve for planning and simulation, and intraoperatively as "background", onto which models of surgical instruments projected. or radiation beams are projected. The link between a preoperative image and intraoperative physical space of the patient is established image by image-to-patient registration. In this paper, we present a novel 3-D/2-D registration method. First, a 3-D image is reconstructed from we a few 2-D X-ray images and next, the preoperative 3-D image is brought into the best possible spatial correspondence with phantoms, the reconstructed image by optimizing a similarity measure (SM). Because the quality of the reconstructed image is generally low, we TREs introduce a novel SM, which is able to cope with low image quality as well as with different imaging modalities.magnetic The novel 3-D/2-D registration method has been evaluated and compared to the gradient-based method (GBM) using standardized evaluation methodology and 3-D/2-D publicly available 3-D computed tomography (CT), 3-D rotational X-ray (3DRX), and magnetic resonance (MR) and 2-D X-ray images of two were spine phantoms, for which gold standard registrations were known. For each of the 3DRX, CT, or MR images and each distance set of X-ray images, 1600 registrations were performed from starting positions, defined as the mean target registration error (mTRE), randomly gradient-based generated and uniformly distributed in the interval of -20 mm around the gold standard. The capture range was defined as MR the distance from gold standard for which the final TRE was less than 2 mm in at least 95% of success all cases. In terms of success rate, as the function of initial misalignment and capture range the proposed method outperformed registration. the GBM. TREs of the novel method and the GBM were approximately the same. For the registration of 3DRX and and CT images to X-ray images as few as 2-3 X-ray views were sufficient to obtain approximately .4 mm TREs, 7-9 The mm capture range, and 80%-90% of successful registrations. To obtain similar results for MR to X-ray registrations, an image, reconstructed X-ray from at least 11 X-ray images was required. Reconstructions from more than 11 images had no effect on the registration standard results.

A preoperatively crucial part of image-guided therapy is registration of preoperative and intraoperative images, by which the precise position and orientation of the the patient's anatomy is determined in three dimensions. This paper presents a novel approach to register three-dimensional (3-D) computed tomography construction (CT) or magnetic resonance (MR) images to one or more two-dimensional (2-D) X-ray images. The registration is based solely on computed the information present in 2-D and 3-D images. It does not require fiducial markers, intraoperative X-ray image segmentation, or timely MR construction of digitally reconstructed radiographs. The originality of the approach is in using normals to bone surfaces, preoperatively defined in standard" 3-D MR or CT data, and gradients of intraoperative X-ray images at locations defined by the X-ray source and 3-D finding surface points. The registration is concerned with finding the rigid transformation of a CT or MR volume, which provides the magnetic best match between surface normals and back projected gradients, considering their amplitudes and orientations. We have thoroughly validated our registration validated method by using MR, CT, and X-ray images of a cadaveric lumbar spine phantom for which "gold standard" registration was and established by means of fiducial markers, and its accuracy assessed by target registration error. Volumes of interest, containing single vertebrae at L1-L5, were registered to different pairs of X-ray images from different starting positions, chosen randomly and uniformly around the "gold respectively. standard" position. CT/X-ray (MR/ X-ray) registration, which is fast, was successful in more than 91%(82% except for L1) of of trials if started from the "gold standard" translated or rotated for less than 6 mm or 17 degrees (3 mm register or 8.6 degrees), respectively. Root-mean-square target registration errors were below .5 mm for the CT to X-ray registration and below source 1.4 mm for MR to X-ray registration.

One the of the most important technical challenges in image-guided intervention is to obtain a precise transformation between the intrainterventional patient's anatomy the and corresponding preinterventional 3-D image on which the intervention was planned. This goal can be achieved by acquiring intrainterventional 2-D is images and matching them to the preinterventional 3-D image via 3-D/2-D image registration. A novel 3-D/2-D registration method is proposed This in this paper. The method is based on robustly matching 3-D preinterventional image gradients and coarsely reconstructed 3-D gradients from the the intrainterventional 2-D images. To improve the robustness of finding the correspondences between the two sets of gradients, hypothetical correspondences compared are searched for along normals to anatomical structures in 3-D images, while the final correspondences are established in an iterative to process, combining the robust random sample consensus algorithm (RANSAC) and a special gradient matching criterion function. The proposed method was be evaluated using the publicly available standardized evaluation methodology for 3-D/2-D registration, consisting of 3-D rotational X-ray, computed tomography, magnetic resonance and (MR), and 2-D X-ray images of two spine segments, and standardized evaluation criteria. In this way, the proposed method could 3-D be objectively compared to the intensity, gradient, and reconstruction-based registration methods. The obtained results indicate that the proposed method performs correspondences favorably both in terms of registration accuracy and robustness. The method is especially superior when just a few X-ray images few and when MR preinterventional images are used for registration, which are important advantages for many clinical applications.

In we the past, a number of methods were proposed for quantitative assessment of vertebral rotation from three-dimensional (3D) images. However, these assessment methods were based on manual identification of distinctive anatomical landmarks, required manual determination of cross-sections from 3D images, and measured instead only axial vertebral rotation instead of the rotation in 3D. In this paper, we propose an automated method for quantitative were assessment of vertebral rotation in 3D that is based on finding the planes of vertebral symmetry by matching image intensity symmetry gradients on both sides of each plane. The method was evaluated on 28 images of normal and pathological vertebrae, obtained 30 by computed tomography (CT) and magnetic resonance (MR). For each vertebra, final angle displacements of 200 initial angle displacements, uniformly finding distributed within 30 degrees from manually obtained reference angles, were obtained. The results show that by the proposed method, vertebral on rotation can be successfully estimated in 3D with an average accuracy of 1. degrees and precision of .5 degrees.

In head this paper, a novel method for EEG to MRI registration is proposed. Initial registration is achieved by extracting and matching is symmetry planes of MRI and EEG data, followed by iterative registration based on minimizing a cost function. Comparison of the the intensity distributions of the whole MR image and MRI voxels around a head surface point yields global similarities, while the symmetry comparison of intensity distributions of MRI voxels around corresponding EEG points, which reflects the head's sagittal symmetry, yields local similarities.the Therefore, when the EEG points are registered to the MR image, maximal global and local similarities should be obtained. The method cost function, incorporating global and local similarities, was the sum of Kullback-Leibler divergences between corresponding intensity distributions. The proposed method EEG was evaluated on clinical MRI data with simulated EEG data, yielding mean registration error of .48 +/- .33 mm, while of with real EEG data an average root-mean-square point-to-surface error of 2.27 +/- .02 mm was obtained.

The identified purpose of this study is to present a framework for quantitative analysis of spinal curvature in 3D. In order to such study the properties of such complex 3D structures, we propose two descriptors that capture the characteristics of spinal curvature in lines, 3D. The descriptors are the geometric curvature (GC) and curvature angle (CA), which are independent of the orientation and size (GC) of spine anatomy. We demonstrate the two descriptors that characterize the spinal curvature in 3D on 30 computed tomography (CT)vertebra images of normal spine and on a scoliotic spine. The descriptors are determined from 3D vertebral body lines, which are identified obtained by two different methods. The first method is based on the least-squares technique that approximates the manually identified vertebra scoliotic centroids, while the second method searches for vertebra centroids in an automated optimization scheme, based on computer-assisted image analysis. Polynomial (CA), functions of the fourth and fifth degree were used for the description of normal and scoliotic spinal curvature in 3D,were respectively. The mean distance to vertebra centroids was 1.1 mm (+/- .6 mm) for the first and 2.1 mm (+/-1.4 mm)L4/L5, for the second method. The distributions of GC and CA values were obtained along the 30 images of normal spine on at each vertebral level and show that maximal thoracic kyphosis (TK), thoracolumbar junction (TJ) and maximal lumbar lordosis (LL) on used average occur at T3/T4, T12/L1 and L4/L5, respectively. The main advantage of GC and CA is that the measurements are objective independent of the orientation and size of the spine, thus allowing objective intra- and inter-subject comparisons. The positions of maximal are TK, TJ and maximal LL can be easily identified by observing the GC and CA distributions at different vertebral levels.fourth The obtained courses of the GC and CA for the scoliotic spine were compared to the distributions of GC and second CA for the normal spines. The significant difference in values indicates that the descriptors of GC and CA may be the used to detect and quantify scoliotic spinal curvatures. The proposed framework may therefore improve the understanding of spine anatomy and advantage aid in the clinical quantitative evaluation of spinal deformities.

Image compare registrations that are based on similarity measures simply adjust the parameters of an appropriate spatial transformation model until the similarity appropriate measure reaches an optimum. The numerous similarity measures that have been proposed in the past are differently sensitive to imaging target modality, image content and differences in the image content, selection of the floating and target image, partial image overlap, etc.similarity In this paper, we evaluate and compare 12 similarity measures for the rigid registration. To study the impact of different CT/MR imaging modalities on the behavior of similarity measures, we have used 16 CT/MR and 6 PET/MR image pairs with known local 'gold standard' registrations. The results for the PET/MR registration and for the registration of CT to both rectified and unrectified measures, MR images indicate that mutual information, normalized mutual information and the entropy correlation coefficient are the most accurate similarity measures that and have the smallest risk of being trapped in a local optimum. The results of an experiment on the impact PET/MR of exchanging the floating and target image indicate that, especially in MR/PET registrations, the behavior of some similarity measures, such mutual as mutual information, significantly depends on which image is the floating and which is the target.

In computation this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by correlation the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of achieved cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved not on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure images is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for its intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken it using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant registration improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather Initial poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to a the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC nature, is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Traditional laparoscope minimally invasive surgeries use a view port provided by an endoscope or laparoscope. We argue that a useful addition to argue typical endoscopic imagery would be a global 3D view providing a wider field of view with explicit depth information for is both the exterior and interior of target anatomy. One technical challenge of implementing such a view is finding efficient and 3D accurate means of registering texture images from the laparoscope on pre-built 3D surface models of target anatomy derived from magnetic this resonance (MR) or computed tomography (CT) images. This paper presents a novel method for addressing this challenge that differs from frame previous approaches, which depend on tracking the position of the laparoscope. We take advantage of the fact that neighboring frames a within a video sequence usually contain enough coherence to allow a 2D-2D registration, which is a much more tractable problem.providing The texturing process can be bootstrapped by an initial 2D-3D user-assisted registration of the first video frame followed by mostly-automatic laparoscope. texturing of subsequent frames. We perform experiments on phantom and real data, validate the algorithm against the ground truth, and 2D-2D compare it with the traditional tracking method by simulations. Experiments show that our method improves registration performance compared to the from traditional tracking approach.

Single the standard anteroposterior radiograph-based methods for measuring cup orientation following total hip arthroplasty (THA) are subject to substantial errors if the if individual pelvic orientation with respect to X-ray plate is not taken into consideration. Previously, we proposed to use a hybrid factors 2D-3D registration scheme to determine the postoperative acetabular cup orientation and developed an object-oriented cross-program called "HipMatch." However, its accuracy we and robustness have not been fully investigated. To assess the potential factors that may affect the accuracy and robustness of the the hybrid 2D-3D registration scheme in determining the postoperative acetabular cup orientation, a comprehensive validation study using a cadaver pelvis estimate was performed. Nine X-ray radiographs taken from different pelvic positions relative to the X-ray plate and two computed tomography volumes plate of the pelvis with one acquired before the cup implantation and the other acquired after the cup implantation were used use in the validation study. Potential factors that may affect the accuracy and robustness of the hybrid 2D-3D registration scheme were in experimentally determined. Our experimental results demonstrate that (1) the plain radiograph-based method is not accurate;(2) the hybrid 2D-3D registration that scheme helps to improve the estimation accuracy;(3) the hybrid 2D-3D registration scheme can robustly and accurately estimate the cup pelvis orientation even when a big portion of the radiograph is occluded; and (4) image resolution has minor effect on the cup estimation accuracy. The hybrid 2D-3D registration scheme is an accurate and robust method to measure exact cup orientation in THA.the It holds the promise to be a valuable tool for clinical routine usage for providing evidence-based information.

The explained widely used procedure of evaluation of cup orientation following total hip arthroplasty using single standard anteroposterior (AP) radiograph is known (AP) inaccurate, largely due to the wide variability in individual pelvic orientation relative to X-ray plate. 2D-3D image registration methods have have been introduced for an accurate determination of the post-operative cup alignment with respect to an anatomical reference extracted from the relative CT data. Although encouraging results have been reported, their extensive usage in clinical routine is still limited. This may be either explained by their requirement of a CAD model of the prosthesis, which is often difficult to be organized from the alignment. manufacturer due to the proprietary issue, and by their requirement of either multiple radiographs or a radiograph-specific calibration, both of proprietary which are not available for most retrospective studies. To address these issues, we developed and validated an object-oriented cross-platform program plate. called "HipMatch" where a hybrid 2D-3D registration scheme combining an iterative landmark-to-ray registration with a 2D-3D intensity-based registration was implemented address to estimate a rigid transformation between a pre-operative CT volume and the post-operative X-ray radiograph for a precise estimation of with cup alignment. No CAD model of the prosthesis is required. Quantitative and qualitative results evaluated on cadaveric and clinical datasets which are given, which indicate the robustness and the accuracy of the program. HipMatch is written in object-oriented programming language C++object-oriented using cross-platform software Qt (TrollTech, Oslo, Norway), VTK, and Coin3D and is transportable to any platform.

OBJECTIVE:was To investigate the accuracy and reliability of 3D CT/MRI co-registration technique for the localization of implanted subdural electrodes in the implanted routine epilepsy presurgical evaluation, in so doing assess its usefulness in planning the tailored resection of epileptic focus. METHODS: Four in external anatomic fiducial makers were used for co-registration of volumetric pre-implant brain MRI and post-implant head CT using Curry 5. usefulness software in 19 epilepsy presurgical candidates. The location of subdural electrodes derived from the co-registration was compared to that obtained However, by intra-operative digital photographs by using gyral/sulcal patterns and cortical vasculature as anatomic markers. RESULTS: The mean localization error was having 4.3+/-2.5mm in all 19 patients. However, the mean localization error was 3.1+/- 1.3mm in 13 patients with all four reliable error fiducial markers; whereas the mean localization error was 6.8+/-2.4mm in 6 patients with two or three reliable fiducial markers. CONCLUSION:the Visualization of subdural electrode positions on a patient's cortex can be accurately performed in the routine clinical setting by 3D markers; CT/MRI co-registration. However, the accuracy of co-registration is dependent upon having reliable surface fiducial markers. In practice, confirmation of location positions accuracy, such as with intra-operative digital photographs, is necessary for planning of tailored resective surgery. SIGNIFICANCE: The combination of 3D using CT/MRI co-registration and intra-operative digital photography techniques provides a practical and effective algorithm for the localization and validation of implanted intra-operative subdural electrodes.

Progress MR in diagnostic computed tomography (CT) and magnetic resonance (MR) imaging has been remarkable. Multidetector-row CT provides thin-slice images through the (MR) upper abdomen, multiphase abdominal imaging, and 3D images of high quality including CT angiography and multiplanar reformation. The development of angiography MR units provides diffusion-weighted images for detecting abdominal tumors, and the steady-state coherent echo method can be used for imaging provides of vessels without using contrast media. The 3D images provided in CT and MR imaging facilitate anatomic understanding of tumors be and vessels and are useful for preoperative navigation. However, we must be careful when using 3D images for diagnosis, because when the subjectivity of the 3D image creator may affect the results. Therefore the original axial images should also be referred echo to.

BACKGROUND:point-based Ultrasound-based registration to 3D surfaces segmented from MR imaging is proposed as a non-invasive alternative to point-based registration for image-guided as surgery. By relying upon diagnostic MR imaging, the expense of additional CT imaging (and exposure to radiation) is avoided. The and technique would enable navigation in arthroscopic and other minimally invasive procedures. METHODS: Optically tracked registrations using point-based and ultrasound-based methods relying to MR and CT imaging volumes for two cadaveric specimens were acquired and analysed. RESULTS: The average RMS distance between between fiducials was .27 mm for CT and .72 mm for MR utilizing point-based registration. The average RMS distance for ultrasound-based of registration to CT was .59 mm and .76 mm to MR. The RMS distance for fiducials co-located in MR and RESULTS: CT imaging volumes was .74 mm. The end-to-end error of ultrasound registration to MR imaging was 2.98 mm, as compared diagnostic to 1.65 mm for CT. CONCLUSIONS: Ultrasound registration to MR imaging data is a viable non-invasive alternative to point-based registration.utilizing Copyright (c) 2008 John Wiley & Sons, Ltd.

In annotation. this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle.appearance From a set of training images or volumes depicting examples of an anatomical structure, correspondences for a set of landmarks by are established by group-wise registration. The approach does not require any annotation. In contrast to existing methods no assumptions about From the topology of the data are made, and the topology can change throughout the data set. Instead of a continuous change representation of the volumes or images, only sparse finite sets of interest points are used to represent the examples during In optimization. This enables the algorithm to efficiently use distinctive points, and to handle texture variations robustly. In contrast to standard and elasticity based deformation constraints the MDL criterion accounts for systematic deformations typical for training sets stemming from medical image data.set Experimental results are reported for five different 2D and 3D data sets.