Fourier registration of three-dimensional brain MR images: Exploiting the axis of rotation

We have developed a novel algorithm to register three-dimensional MR images that have undergone rigid body motion. The most interesting feature of the algorithm is that it reduces a general three-dimensional rotation to a simple planar rotation by finding the axis of rotation. The algorithm, which is a nontrivial three-dimensional extension of existing Fourier registration algorithms, has been tested on 30 artificially misaligned MR images of a phantom, four artificially misaligned MR images of a brain, and one case of actual patient motion. The algorithm successfully registered every image. The registration error for a voxel 10 cm from the origin for the artificially misaligned phantom images was 2.8 mm at most and had a mean of 1.2 mm and standard deviation of .7 mm. The registration parameters for the images contaminated by actual patient motion were similar to that from an established image registration algorithm. The results indicate that the algorithm is accurate, reliable, and fast. The rigid body model requires the brain to be segmented from MR images of the head before registration.     

Comparison and evaluation of rigid, affine, and nonrigid registration of breast MR images.

PURPOSE: A new nonrigid registration method, designed to reduce the effect of movement artifact in subtraction images from breast MR, is compared with existing rigid and affine registration methods. METHOD: Nonrigid registration was compared with rigid and affine registration methods and unregistered images using 54 gadolinium-enhanced 3D breast MR data sets. Twenty-seven data sets had been previously reported normal, and 27 contained a histologically proven carcinoma. The comparison was based on visual assessment and ranking by two radiologists. RESULTS: When analyzed by two radiologists independently, all three registration methods gave better-quality subtraction images than unregistered images (p < 0.01), but nonrigid registration gave significantly better results than the rigid and affine registration methods (p < 0.01). There was no significant difference between rigid and affine registration methods. CONCLUSION: Nonrigid registration significantly reduces the effects of movement artifact in subtracted contrast-enhanced breast MRI. This may enable better visualization of small tumors and those within a glandular breast.     

Bone-subtraction CT angiography: evaluation of two different fully automated image-registration procedures for interscan motion compensation

BACKGROUND AND PURPOSE: Bone-subtraction techniques have been shown to enhance CT angiography (CTA) interpretation, but motion can lead to incomplete bone removal. The aim of this study was to evaluate 2 novel registration techniques to compensate for patient motion. MATERIALS AND METHODS: Fifty-four patients underwent bone-subtraction CTA (BSCTA) for the evaluation of the neck vessels with 64-section CT. We tested 3 different registration procedures: pure rigid registration (BSCTA), slab-based registration (SB-BSCTA), and a partially rigid registration (PR-BSCTA) approach. Subtraction quality for the assessment of different vascular segments was evaluated by 2 examiners in a blinded fashion. The Cohen kappa test was applied for interobserver variability, and the Wilcoxon signed rank test, for differences between the procedures. Motion between the corresponding datasets was measured and plotted against image-quality scores. RESULTS: Algorithms with motion compensation revealed higher image-quality scores (SB-BSCTA, mean 4.31; PR-BSCTA, mean 4.43) than pure rigid registration (BSCTA, mean 3.88). PR-BSCTA was rated superior to SB-BSCTA for the evaluation of the cervical internal and external carotid arteries (P<.001), whereas there was no significant difference for the other vessels (P=.157-.655). Both algorithms were clearly superior to pure rigid registration for all vessels except the basilar and ophthalmic artery. Interobserver agreement was high (kappa=0.46-0.98). CONCLUSION: Bone-subtraction algorithms with motion compensation provided higher image-quality scores than pure rigid registration methods, especially in cases with complex motion. PR-BSCTA was rated superior to SB-BSCTA in the visualization of the internal and external carotid arteries.     

Robust rigid registration of retinal angiograms through optimization

Retinal fundus photographs are employed as standard diagnostic tools in ophthalmology. Serial photographs of the flow of fluorescein and indocyanine green (ICG) dye are used to determine the areas of the retinal lesions. For objective measurements of features, the registration of the images is a necessity. In this paper, we employ optimization techniques for registration with the help of 2-parameter translational motion model of retinal angiograms, based on non-linear pre-processing (Wiener filtering and morphological gradient) and computation of the similarity criteria for the alignment of the two gradient images for any given rigid transformation. The optimization methods are effectively employed to minimize the similarity criterion.

The presence of noise, the variations in the background and the temporal variation of the fluorescence level pose serious problems in obtaining a robust registration of the retinal images. Moreover, local search strategies are not robust in the case of ICG angiograms, even if one uses a multiresolution approach.

The present work makes a systematic comparison of different optimization techniques, namely the minimization method derived from the optical flow formulation, the Nelder-Mead local search and the HCIAC ant colony metaheuristic, each optimizing a similarity criterion for the gradient images. The impact of the resolution and median filtering of gradient image is studied and the robustness of the approaches is tested through experimental studies, performed on macular fluorescein and ICG angiographies.

Our proposed optimization techniques have shown interesting results especially for high resolution difficult registration problems. Moreover, this approach seems promising for affine (6-parameter motion model) or elastical registrations.     

Postacquisition detection of tumor motion in the lung and upper abdomen using list-mode PET data: a feasibility study.

One of the main degrading factors in the quality of oncologic PET images of the thorax and upper abdomen is respiratory motion of tumors. One method to reduce this effect is the acquisition of PET data in gated mode. A second method is the correction of studies for motion. Motion registration is essential in both cases. We report a method using list-mode data to detect the craniocaudal (z) movement of thoracic and abdominal lesions without using any external gating device. The aim of this study was to show the feasibility of applying this method to patient data. METHODS: For 10 patients with lesions in the lung or upper abdominal organs, images for short time bins of 250, 500, and 750 ms were reconstructed. A volume of interest, which was manually defined in a summed image around the structure of interest, was projected to each time bin. The center of mass of the activity distribution in this volume of interest was determined for each case. The curves of the z-coordinate of the center of mass (z(COM)) over the time were analyzed and compared with respiration curves obtained by a pressure-sensitive belt. RESULTS: In 7 of the 10 patients, movement of the lesion was registered in good accordance with the pressure belt. In the 3 remaining patients, no changes in the center of mass due to respiration could be detected, most likely because of minimal respiratory motion. The maximal difference in z(COM) for a lesion that was detected within the 10-min acquisition was 18.5 mm. For 7 of the 10 patients, the mean value for each respiration amplitude was between 11.0 and 2.0 mm. CONCLUSION: We have shown the feasibility of registering movement of high-uptake lesions without the use of any external device that may restrain the patient. Furthermore, unlike external sensors, this method quantifies internal motion and, thus, is a promising base for correction methods.     

Optimal 3D reconstruction of coronary arteries for 3D clinical assessment

A novel method is presented for 3D reconstruction of the coronary arteries. The algorithm refines the point correspondences between the arteries visible in a pair of monoplane X-ray fluoroscopy images acquired at different incidences. Traditional computer vision techniques use the RANSAC methods to discard outliers in a list of corresponding points. However, as these methods work for rigid motion primarily, we introduce a curvature constraint that relates the 2D and 3D Frenet information of the coronary artery centerlines. This constraint takes into account non-rigid movement of the arteries and also serves as a refinement tool to discard potential outlier points. Results show that for synthetic experiments with left-right anterior oblique (LAO/RAO) and posterior-left lateral (PA/LAT) viewing angles, the average 3D RMS errors are respectively 3.1mm and 1.9mm for the RANSAC method, and decrease to 2.8mm and 1.1mm by using our curvature constraint methodology. Similarly, clinical validation is performed on two datasets and the average 2D retroprojection errors are 3.34pixels and 2.24pixels, respectively.     

Prospective acquisition correction for head motion with image-based tracking for real-time fMRI.

In functional magnetic resonance imaging (fMRI) head motion can corrupt the signal changes induced by brain activation. This paper describes a novel technique called Prospective Acquisition CorrEction (PACE) for reducing motion-induced effects on magnetization history. Full three-dimensional rigid body estimation of head movement is obtained by image-based motion detection to a high level of accuracy. Adjustment of slice position and orientation, as well as regridding of residual volume to volume motion, is performed in real-time during data acquisition. Phantom experiments demonstrate a high level of consistency (translation < 40 microm; rotation < 0.05 degrees ) for detected motion parameters. In vivo experiments were carried out and they showed a significant decrease of variance between successively acquired datasets compared to retrospective correction algorithms.     

Motion correction for myocardial T1 mapping using image registration with synthetic image estimation

Quantification of myocardial T1 relaxation has potential value in the diagnosis of both ischemic and nonischemic cardiomyopathies. Image acquisition using the modified Look-Locker inversion recovery technique is clinically feasible for T1 mapping. However, respiratory motion limits its applicability and degrades the accuracy of T1 estimation. The robust registration of acquired inversion recovery images is particularly challenging due to the large changes in image contrast, especially for those images acquired near the signal null point of the inversion recovery and other inversion times for which there is little tissue contrast. In this article, we propose a novel motion correction algorithm. This approach is based on estimating synthetic images presenting contrast changes similar to the acquired images. The estimation of synthetic images is formulated as a variational energy minimization problem. Validation on a consecutive patient data cohort shows that this strategy can perform robust nonrigid registration to align inversion recovery images experiencing significant motion and lead to suppression of motion induced artifacts in the T1 map.     

Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI.

Patient motion and image distortion induced by eddy currents cause artifacts in maps of diffusion parameters computed from diffusion-weighted (DW) images. A novel and comprehensive approach to correct for spatial misalignment of DW imaging (DWI) volumes acquired with different strengths and orientations of the diffusion sensitizing gradients is presented. This approach uses a mutual information-based registration technique and a spatial transformation model containing parameters that correct for eddy current-induced image distortion and rigid body motion in three dimensions. All parameters are optimized simultaneously for an accurate and fast solution to the registration problem. The images can also be registered to a normalized template with a single interpolation step without additional computational cost. Following registration, the signal amplitude of each DWI volume is corrected to account for size variations of the object produced by the distortion correction, and the b-matrices are properly recalculated to account for any rotation applied during registration. Both qualitative and quantitative results show that this approach produces a significant improvement of diffusion tensor imaging (DTI) data acquired in the human brain.     

Integrating external beam and prostate seed implant dosimetry for intermediate and high-risk prostate cancer using biologically effective dose: Impact of image registration technique

PURPOSECombining external beam radiation therapy (EBRT) and prostate seed implant (PSI) is efficacious in treating intermediate- and high-risk prostate cancer at the cost of increased genitourinary toxicity. Accurate combined dosimetry remains elusive due to lack of registration between treatment plans and different biological effect. The current work proposes a method to convert physical dose to biological effective dose (BED) and spatially register the dose distributions for more accurate combined dosimetry.METHODS AND MATERIALSA PSI phantom was CT scanned with and without seeds under rigid and deformed transformations. The resulting CTs were registered using image-based rigid registration (RI), fiducial-based rigid registration (RF), or b-spline deformable image registration (DIR) to determine which was most accurate. Physical EBRT and PSI dose distributions from a sample of 91 previously-treated combined-modality prostate cancer patients were converted to BED and registered using RI, RF, and DIR. Forty-eight (48) previously-treated patients whose PSI occurred before EBRT were included as a “control” group due to inherent registration. Dose-volume histogram (DVH) parameters were compared for RI, RF, DIR, DICOM, and scalar addition of DVH parameters using ANOVA or independent Student's t tests (α = 0.05).RESULTSIn the phantom study, DIR was the most accurate registration algorithm, especially in the case of deformation. In the patient study, dosimetry from RI was significantly different than the other registration algorithms, including the control group. Dosimetry from RF and DIR were not significantly different from the control group or each other.CONCLUSIONSCombined dosimetry with BED and image registration is feasible. Future work will utilize this method to correlate dosimetry with clinical outcomes.     

Registration of emission and transmission whole-body scintillation-camera images.

In this work, a method for registration of whole-body (WB) scintillation-camera images is presented. The primary motive for the development is to perform activity quantification using the conjugate view method on an image basis. Accurate image registration is required for sequential anterior and posterior scans, for serial emission images for analysis of the biokinetics, and for transmission and emission images for a pixel-based attenuation correction. METHODS: Registration is performed by maximization of the mutual information. The spatial transformation has been tailored for the registration of WB images and is composed of global and local transformations, including rigid, projective, and curved transformations. A coarse registration is first performed using cross-correlation and direct pixel scaling. Optimization is then performed in a sequence, beginning with the 2 legs independently, followed by the upper body and head. Evaluation is performed for clinical images of an (131)I-labeled monoclonal antibody and for Monte Carlo-simulated images. An anthropomorphic WB computer phantom, which has been especially modified to match the patient position during WB scanning, is used for the simulations. RESULTS: For simulated images, registration errors are within 1 pixel (<3.6 mm) for a sufficient image count level. Separate evaluation of the influence of noise shows that the errors increase below a total image count of approximately 10(5) (signal-to-noise ratio, approximately 4). For clinical evaluations, the deviations between point markers are 9 +/- 5 mm. CONCLUSION: An automatic registration method for WB images has been developed, which is applicable to emission-emission and transmission-emission registration. This method has been applied in more than 50 clinical studies and has shown to be robust and reliable.     

Reduction of respiratory motion artifacts in transverse relaxation rate (R2) images of the liver.

An empirical motion artifact suppression technique has been developed to reduce the respiratory motion artifacts in axial single spin-echo magnetic resonance (MR) images of the liver post-acquisition. The correction scheme is based on the observation that the dominant motion artifacts within abdominal MR images are ghosts that follow the profile and signal intensity of high signal intensity boundaries, such as those for the subcutaneous fat along the anterior abdominal wall. The technique is applied to the reduction of respiratory motion artifacts in a spin echo image series of the liver of an iron-loaded patient and of a manganese chloride phantom subject to respiratory motion. Subsequent improvements to transverse relaxation rate (R2) image analysis are then demonstrated on the motion-corrected spin echo images, illustrating the utility of the technique for application in the R2 image-based measurement and mapping of liver iron concentration.     

Mutual information-based multimodal image registration using a novel joint histogram estimation

Mutual information (MI)-based image registration has been proved to be very effective in multimodal medical image applications. For computing the mutual information between two images, the joint histogram needs to be estimated. As we know, the joint histogram estimation through linear interpolation and partial volume (PV) interpolation methods may result in the emergency of the local extreme in mutual information registration function. The local extreme is likely to hamper the optimization process and influence the registration accuracy. In this paper, we present a novel joint histogram estimation method (HPV) by using an approximate function of Hanning windowed sinc as kernel function of partial volume interpolation. We apply it to both rigid registration and non-rigid registration. In addition, we give a new method estimating the gradient of mutual information with respect to the model parameters during non-rigid registration. By the experiments on both synthetic and real images, it is clearly shown that the new algorithm has the ability to reduce the local extreme, and the registration accuracy is improved.     

Computer-aided intrapatient comparison of brain SPECT images: the gray-level normalization issue applied to children with epilepsy.

A tool was developed for automated intrapatient comparison of brain SPECT images, with specific emphasis on gray-level normalization. METHODS: Ictal and interictal (99m)Tc-ethyl cysteinate dimer SPECT images were acquired for 6 children with partial epilepsy (age range, 2-10 y). For each patient, 3-dimensional rigid geometric ictal-to-interictal image registration optimizing different classic criteria (correlation coefficient, ratio uniformity) in a multiscale translation-rotation 6-parameter space was first performed. Gray-level normalization was then performed with different methods, using a 1- or 2-parameter linear model. In the 1-parameter case, the scaling factor was equal to the interictal-to-ictal ratio of the maximum, mean, or median values calculated within different reference volumes (whole brain or cerebellum) or obtained by linear regression between ictal and interictal counts in the brain or by maximizing a robust criterion, the number of deterministic sign changes in the subtraction images. In the 2-parameter case, the scaling factor and additive constant were estimated using these last 2 methods. For each patient, registration validity and normalization plausibility were assessed by considering the correlation scatterplot together with the different normalization lines and by comparing interictal and registered normalized ictal images using a twin display (with isocontours) in the 3 orthogonal planes. Three-dimensional volumes of interest could be selected on coupled interictal-subtraction images for further focused numeric comparison. RESULTS: After a satisfactory and stable geometric registration with both criteria, the different normalization methods led to similar subtraction images for 5 of 6 patients, except the maxima ratio, which gave noticeably different results in 2 patients. For the remaining patient, with highly dissimilar ictal-interictal images, the maxima ratio normalization was obviously wrong and the other 1-parameter methods probably better depicted the data than did the 2-parameter methods. CONCLUSION: When comparing intrapatient brain SPECT images, one should be aware of the potential impact of the gray-level normalization method on clinical interpretation. For ictal-interictal images, simple robust scaling should be recommended. In particular, image maximum should generally not be considered a valid reference, and no additive constant is needed in the linear gray-level normalization model.     

Real-time bronchoscope three-dimensional motion estimation using multiple sensor-driven alignment of CT images and electromagnetic measurements

Bronchoscope three-dimensional motion estimation plays a key role in developing bronchoscopic navigation systems. Currently external tracking devices, particularly electromagnetic trackers with electromagnetic sensors, are increasingly introduced to navigate surgical tools in pre-clinical images. An unavoidable problem, which is to align the electromagnetic tracker to pre-clinical images, must be solved before navigation. This paper proposes a multiple sensor-driven registration method to establish this alignment without using any anatomical fiducials. Although current fiducially free registration methods work well, they limit to the initialization of optimization and manipulating the bronchoscope along the bronchial centerlines, which could be failed easily during clinical interventions. To address these limitations, we utilize measurements of multiple electromagnetic sensors to calculate bronchoscope geometric center positions that are usually closer to the bronchial centerlines than the sensor itself measured positions. We validated our method on a bronchial phantom. The experimental results demonstrate that our idea of using multiple sensors to determine bronchoscope geometric center positions for fiducial-free registration was very effective. Compared to currently available methods in bronchoscope three-dimensional motion estimation, our method reduced fiducial alignment error from at least 6.79 to 4.68–5.26 mm and significantly improved motion estimation or tracking accuracy from at least 5.42 to 3.78–4.53 mm.     

Development of three-dimensional kinematic analysis system for artificial knee implants using X-ray fluoroscopic imaging

To achieve quantitative assessment of 3D dynamic motion of artificial knee implants under clinical conditions, we developed a 3D kinematic analysis system using X-ray fluoroscopic imaging. The 3D pose-estimation technique for knee implants was built on a 2D/3D registration algorithm, which determines the spatial pose for each femoral and tibial component from the knee implant contours and computer-assisted design (CAD) models of the implant. In order to validate the accuracy of the 3D pose estimation and the system, computer simulation and in vitro tests were performed using images of knee implants taken in 10 different poses with respect to X-ray focus. Computer simulation tests showed that the root mean square errors (RMSE) for all variables were less than 1.0 mm 1.0 degrees. In vitro tests showed that the RMSE for translation perpendicular to the X-ray image plane was about 1.5 mm, while the accuracy of the remaining two translational and three rotational variables was found to be sufficient for analyzing knee kinematics. Computation time in 3D pose estimation was then obtained in less than 30 seconds for each frame. In clinical application, dynamic movement in deep knee bending was quantitatively analyzed, and the feasibility and effectiveness of the system was demonstrated.     

Motion corrected free-breathing delayed-enhancement imaging of myocardial infarction using nonrigid registration

PURPOSE: To develop and test an automatic free-breathing, delayed enhancement imaging method with improved image signal-to-noise ratio (SNR). MATERIALS AND METHODS: The proposed approach uses free-breathing, inversion-recovery single-shot fast imaging with steady precession (FISP) delayed-enhancement with respiratory motion compensation based on nonrigid image registration. Motion-corrected averaging is used to enhance SNR. RESULTS: Fully automatic, nonrigid registration was compared to previously validated rigid body registration that required user interaction. The performance was measured using the variance of edge positions in intensity profiles through the myocardial infarction (MI) enhanced region and through the right ventricular (RV) wall. Measured variation of the MI edge was 1.16 +/- 0.71 mm (N = 6 patients; mean +/- SD) for rigid body and 1.08 +/- 0.76 mm for nonrigid registration (no significant difference). On the other hand, significant improvement (P < 0.005) was found in the measurements at the RV edge where the SD was 2.06 +/- 0.56 mm for rigid body and 0.59 +/- 0.22 mm for nonrigid registration. CONCLUSION: The proposed approach achieves delayed enhancement images with high resolution and SNR without requiring a breathhold. Motion correction of free-breathing delayed-enhancement imaging using nonrigid image registration may be implemented in a fully automatic fashion and performs uniformly well across the full field of view (FOV).     

Compensation of breathing motion artifacts for MRI with continuously moving table

Breathing motion is one of the main sources of artifacts in MRI acquisitions that can severely impair diagnosis. In MRI with continuously moving table, the application of common motion compensation approaches such as breath holding or the synchronization of the measurement with the breathing motion can be problematic. In this study, a technique for the reduction of breathing‐motion artifacts for MRI with continuously moving table is presented, which reconstructs motion‐consistent volumes from data acquired during free breathing. Axial images are acquired rapidly compared to the period of the breathing motion and consistently combined using a combination of rigid and nonrigid slice‐to‐volume registration. This new technique is compared to a previously reported artifact reduction method for MRI with continuously moving table that is based on the same acquisition scheme. While the latter method only suppresses ghosting artifacts, the new technique is shown to additionally reduce blurring, misregistrations, and signal cancellations in the reconstructed images. Magn Reson Med 63:701–712, 2010. © 2010 Wiley‐Liss, Inc.     

PET与MRI三维脑图像高精度配准

目的 在PC机上实现高精度的PET与MRI三维脑图像配准。方法 采用最大互信息法对6例患者PET和MRI三维脑图像进行刚体配准。使用归一化互信息作为相似性量度。在互信息计算过程中，使用Powell多参数优化法和Brent一维搜索算法。为加快配准速度，使用了多分辨金字塔方法。采用基于坐标的阈值选取方法对PET图像进行分割预处理，消除星状背景伪影。结果 配准误差平均值为2．6mm，误差中位数平均为2．7mm。结论 配准视觉效果良好，评估证明该算法可达亚体元级配准精度。