全局异常信号环境下基于体素灰度多模医学图像配准研究

目的 在全局异常信号环境下,找出适合于临床应用的、满足精度和鲁棒性要求的基于体素灰度多模医学图像配准相似性测度。方法 结合对各种相似性测度的分析,对无异常信号的实际医学图像,和分别加了随机噪声及全局异常信号的多模医学图像进行配准精度的分析。结果 对各种已有成熟的相似性测度进行理论分析和实验对比研究的基础上,归一化互信息在全局异常信号环境下对多模医学图像进行配准,它们的配准精度和鲁棒性表现都令人满意,能得到准确的配准结果。而基于相关比和互信息的配准方法,不能准确地配准加了全局异常信号的多模医学图像。结论 相比于其他相似性测度,归一化互信息在全局异常信号环境下,是一个能满足配准精度和鲁棒性要求的合适相似性测度。     

Evaluation of Elekta 4D cone beam CT-based automatic image registration for radiation treatment of lung cancer

Objective:

The study was aimed to evaluate the precision of Elekta four-dimensional (4D) cone beam CT (CBCT)-based automatic dual-image registrations using different landmarks for clipbox for radiation treatment of lung cancer.

Methods:

30 4D CBCT scans from 15 patients were studied. 4D CBCT images were registered with reference CT images using dual-image registration: a clipbox registration and a mask registration. The image registrations performed in clinic using a physician-defined clipbox, were reviewed by physicians, and were taken as the standard. Studies were conducted to evaluate the automatic dual registrations using three kinds of landmarks for clipbox: spine, spine plus internal target volume (ITV) and lung (including as much of the lung as possible). Translational table shifts calculated from the automatic registrations were compared with those of the standard.

Results:

The mean of the table shift differences in the lateral direction were 0.03, 0.03 and 0.03 cm, for clipboxes based on spine, spine plus ITV and lung, respectively. The mean of the shift differences in the longitudinal direction were 0.08, 0.08 and 0.08 cm, respectively. The mean of the shift differences in the vertical direction were 0.03, 0.03 and 0.03 cm, respectively.

Conclusion:

The automatic registrations using three different landmarks for clipbox showed similar results. One can use any of the three landmarks in 4D CBCT dual-image registration.

Advance in knowledge:

The study provides knowledge and recommendations for application of Elekta 4D CBCT image registration in radiation therapy of lung cancer.     

Fiducial marker placement for intraoperative spine localization

In recent years, there has been a great increase in the number of cases of image-guided fiducial marker placement for the purposes of stereotactic radiosurgery. At the authors' parent institution, a tertiary referral academic medical center, the placement of fiducial markers has also been used for the purposes of localization before spine surgery. Given the reported prevalence of "wrong-site" surgical intervention documented in the medical literature, particularly involving spinal surgery, the neurosurgical department at the authors' institution has requested the expertise of interventional radiology for assistance in preoperative spine localization. Therefore, there are medicolegal, medical cost, and patient care implications of image-guided fiducial marker placement.     

Acquisition-related motion compensation for digital subtraction angiography

Subtraction methods in angiography are generally applied in order to enhance the visualization of blood vessels by eliminating bones and surrounding tissues from X-ray images. The main limitation of these methods is the sensitivity to patient movement, which leads to artifacts and reduces the clinical value of the subtraction images. In this paper we present a novel method for rigid motion compensation with primary application to road mapping, frequently used in image-guided interventions. Using the general concept of image-based registration, we optimize the physical position and orientation of the C-arm X-ray device, thought of as the rigid 3D transformation accounting for the patient movement. The registration is carried out using a hierarchical optimization strategy and a similarity measure based on the variance of intensity differences, which has been shown to be most suitable for fluoroscopic images. Performance evaluation demonstrated the capabilities of the proposed approach to compensate for potential intra-operative patient motion, being more resilient to the fundamental problems of pure image-based registration.     

Registration of three-dimensional MR and CT studies of the cervical spine

A three-dimensional image registration technique for CT and MR studies of the cervical spine was evaluated for feasibility and efficacy. Registration by means of external fiducial markers was slightly more accurate than registration by anatomic landmarks. The interrelationships between bony (eg, neural foramina) and soft tissue structures (eg, nerve roots) in the cervical spine were more conspicuous on registered images than on conventional displays. Registration of CT and MR images may be used to examine more precisely the relationships between bony and soft tissue structures of the cervical spine.     

Assessment of a technique for 2D-3D registration of cerebral intra-arterial angiography

This study assesses the ability of a computer algorithm to perform automated 2D-3D registrations of digitally subtracted cerebral angiograms. The technique was tested on clinical studies of five patients with intracranial aneurysms. The automated procedure was compared against a gold standard manual registration, and achieved a mean registration accuracy of 1.3 mm (SD 0.6 mm). Two registration strategies were tested using coarse (128 x 128 pixel) or fine (256 x 256 pixel) images. The mean registration errors proved similar but registration of the lower resolution images was 3 times quicker (mean registration times 33 s, SD 13 s for low and 150 s SD 48 s for high resolution images). The automated techniques were considerably faster than manual registrations but achieved similar accuracy. The technique has several potential uses but is particularly applicable to endovascular treatment techniques.     

基于体素灰度三维多模医学图像配准中相似性测度的选取

目的：在基于体素灰度医学图像配准领域，找出最适合于临床应用的多模医学图像配准相似性测度。方法：在极端的刚体配准条件下，检验出互相关系数，互信息和相关比相似性测度为适合的相似性测度。同时进一步解释了基于互信息相似性测度的医学图像配准易于陷入局部最优，而基于相关比相似性测度的方法易于保证配准得到全局最优，最后，利用加速的多分辨率配准方案和Powell‘s优化算法，对临床医学图像进行了基于相关比相似性测度的多模图像配准试验。结果：通过临床医学专家的判断，利用相关比相似性测度进行多模医学图像配准，安全能满足临床的要求，进行MR／CT，MR／PET三维多模医学图像配准时效果非常理想，结论：相比于其他相似性测度，互相关比相似性测度在基于体素灰度，三维多模医学图像配准领域，是一个更为适宜和准确的相似性测度。     

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.     

Three-dimensional reconstruction and fusion for multi-modality spinal images.

Medical diagnosis can benefit from the complementary information in different modality images. Multi-modal image registration and fusion is an essential task in numerous three-dimensional (3D) medical image-processing applications. Registered images are not only providing more correlative information to aid in diagnosis, but also assisting with the planning and monitoring of both surgery and radiotherapy. This research is directed at registering different images captured from Computed Tomography (CT) and Magnetic Resonance (MR) imaging devices, respectively, to acquire more thorough information for disease diagnosis. Because MR bone model segmentation is difficult, this research used a 3D model obtained from CT images. This model accomplishes image registration by optimizing the gradient information accumulated around the bony boundary areas with respect to the 3D model. This system involves pre-processing, 2D segmentation, 3D registration, fusion and sub-system rendering. This method provides desired image operation, robustness verification, and multi-modality spinal image registration accuracy. The proposed system is useful in observing the foramen and nerve root. Because the registration can be performed without external markers, a better choice for clinical usage is provided for lumbar spine diagnosis.     

Evaluation of the correlation between prostatic displacement and rectal deformation using the Dice similarity coefficient of the rectum

To estimate the relationship between the three-dimensional (3D) displacement error of the prostate and rectal deformation for reduction of deviation between the planned and treatment dose, using multiple acquisition planning CT (MPCT) and the Dice similarity coefficient (DSC) for rectal deformation for treatment of patients with prostate cancer. The 3D displacement error between the pelvic bone and a matching fiducial marker was calculated using MPCT in 24 patients who underwent prostate volumetric-modulated arc therapy for prostate cancer. We calculated the 3D displacement error between the pelvic bone and a matching fiducial marker on MPCT. The correlation of the 3D displacement error with the DSC of the rectum, calculated from MPCT images, was evaluated based on deformable image registration. The 3D displacement error of the prostate showed a slight correlation between MPCT and cone-beam computed tomography (adjusted r² = 0.241). The 3D displacement error, based on the pelvic bone and a fiducial marker on MPCT images, showed a moderate correlation with the DSC of the rectum (adjusted r² = 0.645) and was improved by a mean of 3.94 mm, based on MPCT, during the treatment period. The 3D displacement error on MPCT correlates with the 3D displacement error of daily cone-beam computed tomography; optimal selection of MPCT can potentially facilitate on-board setup of prostate patients to enable more accurate radiotherapy. The advance information of the 3D displacement error and rectal deformation is useful for optimal planning CT that can minimize the deviation between the planned dose and the treatment dose in patients receiving treatment for prostate cancer.     

Validation of fully automatic brain SPET to MR co-registration

Fully automatic co-registration of functional to anatomical brain images using information intrinsic to the scans has been validated in a clinical setting for positron emission tomography (PET), but not for single-photon emission tomography (SPET). In this paper we evaluate technetium-99m hexamethylpropylene amine oxime to magnetic resonance (MR) co-registration for five fully automatic methods. We attached six small fiducial markers, visible in both SPET and MR, to the skin of 13 subjects. No increase in the radius of SPET acquisition was necessary. Distortion of the fiducial marker distribution observed in the SPET and MR studies was characterised by a measure independent of registration and three subjects were excluded on the basis of excessive distortion. The location of each fiducial marker was determined in each modality to sub-pixel precision and the inter-modality distance was averaged over all markers to give a fiducial registration error (FRE). The component of FRE excluding the variability inherent in the validation method was estimated by computing the error transformation between the arrays of MR marker locations and registered SPET marker locations. When applied to the fiducial marker locations this yielded the surface registration error (SRE), and when applied to a representative set of locations within the brain it yielded the intrinsic registration error (IRE). For the best method, mean IRE was 1.2 mm, SRE 1.5 mm and FRE 2.4 mm (with corresponding maxima of 3.3, 4.3 and 5.0 mm). All methods yielded a mean IRE <3 mm. The accuracy of the most accurate fully automatic SPET to MR co-registration was comparable with that published for PET to MR. With high standards of calibration and instrumentation, intra-subject cerebral SPET to MR registration accuracy of <2 mm is attainable.     

Validation of fully automatic brain SPET to MR co-registration

Fully automatic co-registration of functional to anatomical brain images using information intrinsic to the scans has been validated in a clinical setting for positron emission tomography (PET), but not for single-photon emission tomography (SPET). In this paper we evaluate technetium-99m hexamethylpropylene amine oxime to magnetic resonance (MR) co-registration for five fully automatic methods. We attached six small fiducial markers, visible in both SPET and MR, to the skin of 13 subjects. No increase in the radius of SPET acquisition was necessary. Distortion of the fiducial marker distribution observed in the SPET and MR studies was characterised by a measure independent of registration and three subjects were excluded on the basis of excessive distortion. The location of each fiducial marker was determined in each modality to sub-pixel precision and the inter-modality distance was averaged over all markers to give a fiducial registration error (FRE). The component of FRE excluding the variability inherent in the validation method was estimated by computing the error transformation between the arrays of MR marker locations and registered SPET marker locations. When applied to the fiducial marker locations this yielded the surface registration error (SRE), and when applied to a representative set of locations within the brain it yielded the intrinsic registration error (IRE). For the best method, mean IRE was 1.2 mm, SRE 1.5 mm and FRE 2.4 mm (with corresponding maxima of 3.3, 4.3 and 5.0 mm). All methods yielded a mean IRE <3 mm. The accuracy of the most accurate fully automatic SPET to MR co-registration was comparable with that published for PET to MR. With high standards of calibration and instrumentation, intra-subject cerebral SPET to MR registration accuracy of <2 mm is attainable. Received 29 May and in revised form 6 October 1999     

Evaluation of Four Volume-Based Image Registration Algorithms

We evaluated 4 volume-based automatic image registration algorithms from 2 commercially available treatment planning systems (Philips Syntegra and BrainScan). The algorithms based on cross correlation (CC), local correlation (LC), normalized mutual information (NMI), and BrainScan mutual information (BSMI) were evaluated with: (1) the synthetic computed tomography (CT) images, (2) the CT and magnetic resonance (MR) phantom images, and (3) the CT and MR head image pairs from 12 patients with brain tumors. For the synthetic images, the registration results were compared with known transformation parameters, and all algorithms achieved accuracy of submillimeter in translation and subdegree in rotation. For the phantom images, the registration results were compared with those provided by frame and marker-based manual registration. For the patient images, the results were compared with anatomical landmark–based manual registration to qualitatively determine how the results were close to a clinically acceptable registration. NMI and LC outperformed CC and BSMI, with the sense of being closer to a clinically acceptable result. As for the robustness, NMI and BSMI outperformed CC and LC. A guideline of image registration in our institution was given, and final visual assessment is necessary to guarantee reasonable results.     

Motion tracking in MR-guided liver therapy by using navigator echoes and projection profile matching

RATIONALE AND OBJECTIVES: Image registration in magnetic resonance (MR) image-guided liver therapy enhances surgical guidance by fusing preoperative multimodality images with intraoperative images, or by fusing intramodality images to correlate serial intraoperative images to monitor the effect of therapy. The objective of this paper is to describe the application of navigator echo and projection profile matching to fast two-dimensional image registration for MR-guided liver therapy. MATERIALS AND METHODS: We obtain navigator echoes along the read-out and phase-encoding directions by using modified gradient echo imaging. This registration is made possible by masking out the liver profile from the image and performing profile matching with cross-correlation or mutual information as similarity measures. The set of experiments include a phantom study with a 2.0-T experimental MR scanner, and a volunteer and a clinical study with a 0.5-T open-configuration MR scanner, and these evaluate the accuracy and effectiveness of this method for liver therapy. RESULTS: Both the phantom and volunteer study indicate that this method can perform registration in 34 ms with root-mean-square error of 1.6 mm when the given misalignment of a liver is 30 mm. The clinical studies demonstrate that the method can track liver motion of up to approximately 40 mm. Matching profiles with cross-correlation information perform better than with mutual information in terms of robustness and speed. CONCLUSION: The proposed image registration method has potential clinical impact on and advantages for MR-guided liver therapy.     

Evaluation of Four Volume-Based Image Registration Algorithms

We evaluated 4 volume-based automatic image registration algorithms from 2 commercially available treatment planning systems (Philips Syntegra and BrainScan). The algorithms based on cross correlation (CC), local correlation (LC), normalized mutual information (NMI), and BrainScan mutual information (BSMI) were evaluated with: (1) the synthetic computed tomography (CT) images, (2) the CT and magnetic resonance (MR) phantom images, and (3) the CT and MR head image pairs from 12 patients with brain tumors. For the synthetic images, the registration results were compared with known transformation parameters, and all algorithms achieved accuracy of submillimeter in translation and subdegree in rotation. For the phantom images, the registration results were compared with those provided by frame and marker-based manual registration. For the patient images, the results were compared with anatomical landmark–based manual registration to qualitatively determine how the results were close to a clinically acceptable registration. NMI and LC outperformed CC and BSMI, with the sense of being closer to a clinically acceptable result. As for the robustness, NMI and BSMI outperformed CC and LC. A guideline of image registration in our institution was given, and final visual assessment is necessary to guarantee reasonable results.     

Co-registration of x-ray and MR fields of view in a hybrid XMR system

PURPOSE: To validate one possible function of a real-time x-ray/MR (XMR) interface in a hybrid XMR system using x-ray images as "scouts" to prescribe the MR slices. MATERIALS AND METHODS: The registration process consists of two steps: 1) calibration, in which the system's geometric parameters are found from fiducial-based registration; and 2) application, in which the x-ray image of a target structure and the estimated geometric parameters are used to prescribe an MR slice to observe the target structure. Errors from the noise in the location of the fiducial markers, and MR gradient nonlinearity were studied. Computer simulations were used to provide guidelines for fiducial marker placement and tolerable error estimation. A least-squares-based correction method was developed to reduce errors from gradient nonlinearity. RESULTS: In simulations with both sources of errors and the correction for gradient nonlinearity, the use of 16 fiducial markers yielded a mean error of about 0.4 mm over a 7200 cm(3) volume. Phantom scans showed that the prescribed target slice hit most of the target line, and that the length visualized was improved with the least-squares correction. CONCLUSION: The use of 16 fiducial markers to co-register XMR FOVs can offer satisfactory accuracy in both simulations and experiments.     

Automatic registration of MR and SPECT images for treatment planning in prostate cancer

RATIONALE AND OBJECTIVES: To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate. MATERIALS AND METHODS: The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2 degree difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists. RESULTS: Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration. CONCLUSION: Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.     

Improving the accuracy of motion quantification using area detector computed tomography for real-time tumor-tracking irradiation in stereotactic ablative radiotherapy

CyberKnife radiotherapy enables tumor-tracking irradiation using positional information regarding the tumor and a fiducial marker in a patient's body. This positional information acts as a surrogate of tumor motion. Therefore, deviations in these movements should be quantitatively estimated and included as an internal margin for radiation treatment planning. This study aimed to investigate variations between the positions of fiducial markers and tumor regions using 320-row area detector computed tomography and to analyze the effectiveness of our proposed method in contouring tumor regions based on the fiducial marker position. To determine the moving tumor volume, a typical single-phase image was selected, and pixel values in other phase images were accumulated. Moreover, a maximum-intensity projection image was created to clarify motion deviations in the tumor volume. To evaluate the delineation accuracy, the dice similarity coefficient and mean distance to agreement were calculated in phase-selected and breath-holding computed tomography. Moving chest phantom images were acquired using helical scanning 4-dimensional computed tomography (H-4DCT) and volumetric scanning 4-dimensional computed tomography (V-4DCT), and the delineation accuracies were compared for each scanning type. The average dice similarity coefficient and mean distance to agreement were degraded in limited-phase images, which cannot represent the hysteretic motion of a tumor. Moreover, deviations in tumor volume with unstable motion reached 71.6% in H-4DCT but only 1.6% in V-4DCT. Our proposed method with V-4DCT using area detector computed tomography can achieve accurate moving tumor delineation and can clarify positional associations between the fiducial marker and tumor under respiratory motion.     

PET-MR image fusion in soft tissue sarcoma: accuracy,reliability and practicality of interactive point-based and automated mutual information techniques

The fusion of functional positron emission tomography (PET) data with anatomical magnetic resonance (MR) or computed tomography images, using a variety of interactive and automated techniques, is becoming commonplace, with the technique of choice dependent on the specific application. The case of PET-MR image fusion in soft tissue is complicated by a lack of conspicuous anatomical features and deviation from the rigid-body model. Here we compare a point-based external marker technique with an automated mutual information algorithm and discuss the practicality, reliability and accuracy of each when applied to the study of soft tissue sarcoma. Ten subjects with suspected sarcoma in the knee, thigh, groin, flank or back underwent MR and PET scanning after the attachment of nine external fiducial markers. In the assessment of the point-based technique, three error measures were considered: fiducial localisation error (FLE), fiducial registration error (FRE) and target registration error (TRE). FLE, which represents the accuracy with which the fiducial points can be located, is related to the FRE minimised by the registration algorithm. The registration accuracy is best characterised by the TRE, which is the distance between corresponding points in each image space after registration. In the absence of salient features within the target volume, the TRE can be measured at fiducials excluded from the registration process. To assess the mutual information technique, PET data, acquired after physically removing the markers, were reconstructed in a variety of ways and registered with MR. Having applied the transform suggested by the algorithm to the PET scan acquired before the markers were removed, the residual distance between PET and MR marker-pairs could be measured. The manual point-based technique yielded the best results (RMS TRE =8.3 mm, max =22.4 mm, min =1.7 mm), performing better than the automated algorithm (RMS TRE =20.0 mm, max =30.5 mm, min =7.7 mm) when registering filtered back-projection PET images to MR. Image reconstruction with an iterative algorithm or registration of a composite emission-transmission image did not improve the overall accuracy of the registration process. We have demonstrated that, in this application, point-based PET-MR registration using external markers is practical, reliable and accurate to within approximately 5 mm towards the fiducial centroid. The automated algorithm did not perform as reliably or as accurately.     

Software for image registration: algorithms,accuracy, efficacy

Image registration is finding increased clinical use both in aiding diagnosis and guiding therapy. There are numerous algorithms for registration, which all involve maximizing a measure of similarity between a transformed floating image and a fixed reference image. The choice of the similarity measure depends, to some extent, on the application. Methods based on the use of the joint intensity histogram have become popular because of their flexibility and robustness. A distinction is made between rigid-body and non-rigid transformations. The latter are needed for inter-subject registration or intra-subject registration in cases where the region of the body of interest is not considered rigid. Non-rigid transformation is normally achieved using a global model of the deformation but can also be defined by a set of locally rigid transformations, each constrained to a small block in the image. There is scope for further research on the incorporation of appropriate constraints, especially for the application of non-rigid transformations to nuclear medicine studies. Most of the initial practical concerns regarding image registration have been overcome and there is increasing availability of commercial software. There are several approaches to the validation of registration software, with validation of non-rigid algorithms being particularly difficult. Studies have demonstrated the accuracy on the order of half a pixel for both intra- and inter-modality registration (typically 2 to 3 mm). Although hardware-based registration has now become possible by using dual-modality instruments, software-based registration will continue to play an important role in nuclear medicine.