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ABSTRACT: Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D- 2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of ten patients undergoing cerebral EIGI and established ¿gold standard¿ registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 second. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI.
IEEE transactions on medical imaging. 04/2013;
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Christelle Gendrin,
Primoz Markelj,
Supriyanto Ardjo Pawiro,
Jakob Spoerk,
Christoph Bloch,
Christoph Weber,
Michael Figl,
Helmar Bergmann,
Wolfgang Birkfellner,
Bostjan Likar, Franjo Pernus
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ABSTRACT: A new gold standard data set for validation of 2D/3D registration based on a porcine cadaver head with attached fiducial markers was presented in the first part of this article. The advantage of this new phantom is the large amount of soft tissue, which simulates realistic conditions for registration. This article tests the performance of intensity- and gradient-based algorithms for 2D/3D registration using the new phantom data set.
Intensity-based methods with four merit functions, namely, cross correlation, rank correlation, correlation ratio, and mutual information (MI), and two gradient-based algorithms, the backprojection gradient-based (BGB) registration method and the reconstruction gradient-based (RGB) registration method, were compared. Four volumes consisting of CBCT with two fields of view, 64 slice multidetector CT, and magnetic resonance-T1 weighted images were registered to a pair of kV x-ray images and a pair of MV images. A standardized evaluation methodology was employed. Targets were evenly spread over the volumes and 250 starting positions of the 3D volumes with initial displacements of up to 25 mm from the gold standard position were calculated. After the registration, the displacement from the gold standard was retrieved and the root mean square (RMS), mean, and standard deviation mean target registration errors (mTREs) over 250 registrations were derived. Additionally, the following merit properties were computed: Accuracy, capture range, number of minima, risk of nonconvergence, and distinctiveness of optimum for better comparison of the robustness of each merit.
Among the merit functions used for the intensity-based method, MI reached the best accuracy with an RMS mTRE down to 1.30 mm. Furthermore, it was the only merit function that could accurately register the CT to the kV x rays with the presence of tissue deformation. As for the gradient-based methods, BGB and RGB methods achieved subvoxel accuracy (RMS mTRE down to 0.56 and 0.70 mm, respectively). Overall, gradient-based similarity measures were found to be substantially more accurate than intensity-based methods and could cope with soft tissue deformation and enabled also accurate registrations of the MR-T1 volume to the kV x-ray image.
In this article, the authors demonstrate the usefulness of a new phantom image data set for the evaluation of 2D/3D registration methods, which featured soft tissue deformation. The author's evaluation shows that gradient-based methods are more accurate than intensity-based methods, especially when soft tissue deformation is present. However, the current nonoptimized implementations make them prohibitively slow for practical applications. On the other hand, the speed of the intensity-based method renders these more suitable for clinical use, while the accuracy is still competitive.
Medical Physics 03/2011; 38(3):1491-502. · 2.83 Impact Factor
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Mach. Vis. Appl. 01/2011; 22:197-206.
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Med. Biol. Engineering and Computing. 01/2011; 49:957-966.
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Multimodal Brain Image Analysis, First International Workshop, MBIA 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings; 01/2011
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ABSTRACT: Pellet coating processes are usually driven by fairly well optimized procedures, while coating suspension sprayed on pellets and adverse effects, such as agglomeration, can not be seen during coating process and are only detected at the very end of the process, when it is too late for any adjustments of the coating process. The aim of this study is to evaluate digital visual imaging as process analytical technology (PAT) tool for fluid-bed pellet coating processes. The method accurately estimates spherical diameter, coating thickness and adverse agglomeration of pellets by contactless measurements, classification and analysis of pellets based on digital imaging. Calibration and thorough assessment of the accuracy, precision, stability and speed of the proposed method was performed with high precision bearing balls. The obtained results on real pellets indicated that the method is feasible for real-time controlling, understanding, designing and optimizing of fluid-bed pellet coating processes according to PAT guidance.
European journal of pharmaceutical sciences: official journal of the European Federation for Pharmaceutical Sciences 09/2010; 41(1):156-62. · 2.61 Impact Factor
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ABSTRACT: A new image database with a reference-based standardized evaluation methodology for objective evaluation and comparison of three-dimensional/two-dimensional (3D/2D) registration methods has been introduced.
Computed tomography (CT) images of a male and female from the Visible Human Project were used and 16 subvolumes, each containing one of vertebrae T3-T12 and L1-L5 and the pelvis, were defined from the CTs. Six pairs of 2D fluoroscopic x-ray images from different views, showing the thoracic, lumbar, and pelvic regions, were rendered from the CT data using a ray-casting algorithm with an energy conversion function. Furthermore, a single 13-gauge needle was analytically simulated and projected onto the 2D images. By the novel standardized evaluation methodology, a 3D/2D registration method is evaluated by four evaluation criteria: Accuracy, reliability, robustness, and algorithm complexity.
To demonstrate the usefulness of the proposed data set and the standardized evaluation methodology, a part of the data set was used in an evaluation study of two gradient-based 3D/2D registration methods. It was shown that the use of a failure criterion to calculate the registration accuracy and reliability is not required, since all the information about a registration method can be determined from the estimated distribution of registration errors.
The proposed simulated image data set with quite realistic synthetic 2D images, depicting soft tissues and outliers, is especially suitable for preliminary testing of 3D/2D registration algorithms. Since the aim of this article is to provide objective comparison and unbiased evaluation of 3D/2D registration methods, the standardized evaluation methodology is available upon request from the authors.
Medical Physics 09/2010; 37(9):4643-7. · 2.83 Impact Factor
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ABSTRACT: Every imaging system requires a geometric calibration to yield accurate optical measurements. Geometric calibration typically involves imaging of a known calibration object and finding the parameters of a camera model and a model of optical aberrations. Optical aberrations can vary significantly across the wide spectral ranges of hyperspectral imaging systems, which can lead to inaccurate geometric calibrations if conventional methods were used. We propose a method based on a B-spline transformation field to align the spectral images of the calibration object to the model image of the calibration object. The degree of spatial alignment between the ideal and the spectral images is measured by normalized cross correlation. Geometric calibration was performed on a hyperspectral imaging system based on an acousto-optic tunable filter designed for the near-infrared spectral range (1.0-1.7microm). The proposed method can accurately characterize wavelength dependent optical aberrations and produce transformations for efficient subpixel geometric calibration.
Applied Optics 05/2010; 49(15):2813-8. · 1.41 Impact Factor
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ABSTRACT: Axial vertebral rotation (AVR) of normal and scoliotic vertebrae was measured in computed tomography (CT) images by three observers using different manual and a computerized method.
To analyze 4 manual and a computerized method for measuring AVR in CT images.
Manual measurement of AVR is difficult and error-prone when compared with computerized methods. To the best of our knowledge, a systematic comparison of the established manual with a computerized method has not been performed yet.
AVRs of 14 normal and 14 scoliotic vertebrae from CT images were measured (a) manually using the methods of Aaro and Dahlborn, Spine 1981;6:460-7, Ho et al, Spine 1993;18:1173-7, Krismer et al, J Spinal Disord 1999;12:126-30, and Göçen et al, J Spinal Disord 1998;11:210-4., and (b) automatically using a computerized method, which is based on the evaluation of vertebral symmetry in 2 dimensions (2D) and in 3 dimensions (3D). RESULTS.: The computerized method was most consistent with the method of Aaro and Dahlborn, which also proved to be the most reproducible and reliable manual method. The low overall intraobserver variability (1.1 degrees SD) and interobserver variability (1.8 degrees SD) of the computerized method indicate that the symmetry-based determination of AVR is reproducible and reliable, as the localization of vertebral centroids is the major source of its variability.
The computerized method yielded higher reproducibility and reliability of AVR measurements, indicating that it may represent a feasible alternative to manual methods, moreover because it is also faster and more operator-friendly.
Spine 05/2010; 35(12):E535-41. · 2.08 Impact Factor
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ABSTRACT: Axial vertebral rotation (AVR) of 14 normal and 14 scoliotic vertebrae from magnetic resonance (MR) images was determined by three observers using four manual methods and a computerized method, which were based on the evaluation of vertebral symmetry in two dimensions (2D) and in three dimensions (3D). The method of Aaro and Dahlborn proved to be the manual method with the highest intra-observer (1.7 degrees SD) and inter-observer (1.2 degrees SD) reliabilities, and was also most in agreement with the computerized method (1.3 degrees SD, 1.0 degrees MAD). The computerized method yielded higher intra-observer (1.3 degrees SD) and inter-observer (1.4 degrees SD) reliabilities than the manual methods, indicating it to be an efficient alternative for repeatable and reliable AVR measurements.
European Spine Journal 03/2010; 19(5):774-81. · 1.97 Impact Factor
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ABSTRACT: The most important decisive factor for choosing the robot type is certainly performance to price ratio. A big portion of the final price is usually the cost of development. The robot performance is a combination of inspection quality, autonomy and universality. We can conclude that the flying robot would likely have the smallest performance to price ratio (table I). Namely, this robot, although universal and easy to design, would offer the lowest inspection quality and low inspection autonomy. The development costs would certainly be very high for the climbing robot but the robot would be much more autonomous and could offer better inspection quality. The latter also holds true for the climbing-flying robot, which would probably not be as autonomous as the climbing robot when crossing obstacles but the cost of development should be much lower. In conclusion, the power pick-up system and automatic visual inspection are problems that still need to be solved efficiently for the flying robot, while automatic power line tracking and obstacle avoidance need further improvements to become practically feasible. The climbing robot also needs further developments of the power pick-up system, automatic visual inspection, electromagnetic shielding, robot mechanism and the control system. The proposed climbing-flying concept for power line inspection has not been researched yet, offering a number of specific challenges, such as high communication link bandwidth and reliable system for landing on the conductor. Nevertheless, the proposed concept seems feasible from the practical point of view and because good performance to price ration could be obtained.
03/2010; , ISBN: 978-953-307-030-8
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Biomedical Image Registration, 4th International Workshop, WBIR 2010, Lübeck, Germany, July 11-13, 2010. Proceedings; 01/2010
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Medical Imaging and Augmented Reality - 5th International Workshop, MIAR 2010, Beijing, China, September 19-20, 2010. Proceedings; 01/2010
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20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, Turkey, 23-26 August 2010; 01/2010
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ABSTRACT: We propose a completely automated algorithm for the detection of the spinal centreline and the centres of vertebral bodies and intervertebral discs in images acquired by computed tomography (CT) and magnetic resonance (MR) imaging. The developed methods are based on the analysis of the geometry of spinal structures and the characteristics of CT and MR images and were evaluated on 29 CT and 13 MR images of lumbar spine. The overall mean distance between the obtained and the ground truth spinal centrelines and centres of vertebral bodies and intervertebral discs were 1.8 +/- 1.1 mm and 2.8 +/- 1.9 mm, respectively, and no considerable differences were detected among the results for CT, T(1)-weighted MR and T(2)-weighted MR images. The knowledge of the location of the spinal centreline and the centres of vertebral bodies and intervertebral discs is valuable for the analysis of the spine. The proposed method may therefore be used to initialize the techniques for labelling and segmentation of vertebrae.
Physics in Medicine and Biology 01/2010; 55(1):247-64. · 2.83 Impact Factor
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ABSTRACT: Quantitative evaluation of axial vertebral rotation is essential for the determination of reference values in normal and pathological conditions and for understanding the mechanisms of the progression of spinal deformities. However, routine quantitative evaluation of axial vertebral rotation is difficult and error-prone due to the limitations of the observer, characteristics of the observed vertebral anatomy and specific imaging properties. The scope of this paper is to review the existing methods for quantitative evaluation of axial vertebral rotation from medical images along with all relevant publications, which may provide a valuable resource for studying the existing methods or developing new methods and evaluation strategies. The reviewed methods are divided into the methods for evaluation of axial vertebral rotation in 2D images and the methods for evaluation of axial vertebral rotation in 3D images. Key evaluation issues and future considerations, supported by the results of the overview, are also discussed.
European Spine Journal 03/2009; 18(8):1079-90. · 1.97 Impact Factor
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ABSTRACT: The aim of this paper is to provide a complete overview of the existing methods for quantitative evaluation of spinal curvature from medical images, and to summarize the relevant publications, which may not only assist in the introduction of other researchers to the field, but also be a valuable resource for studying the existing methods or developing new methods and evaluation strategies. Key evaluation issues and future considerations, supported by the results of the overview, are also discussed.
European Spine Journal 03/2009; 18(5):593-607. · 1.97 Impact Factor
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ABSTRACT: One of the most important technical challenges in image-guided intervention is to obtain a precise transformation between the intrainterventional patient's anatomy and corresponding preinterventional 3-D image on which the intervention was planned. This goal can be achieved by acquiring intrainterventional 2-D 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 in this paper. The method is based on robustly matching 3-D preinterventional image gradients and coarsely reconstructed 3-D gradients from the intrainterventional 2-D images. To improve the robustness of finding the correspondences between the two sets of gradients, hypothetical correspondences are searched for along normals to anatomical structures in 3-D images, while the final correspondences are established in an iterative process, combining the robust random sample consensus algorithm (RANSAC) and a special gradient matching criterion function. The proposed method was 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 (MR), and 2-D X-ray images of two spine segments, and standardized evaluation criteria. In this way, the proposed method could be objectively compared to the intensity, gradient, and reconstruction-based registration methods. The obtained results indicate that the proposed method performs favorably both in terms of registration accuracy and robustness. The method is especially superior when just a few X-ray images and when MR preinterventional images are used for registration, which are important advantages for many clinical applications.
IEEE transactions on medical imaging. 01/2009; 27(12):1704-14.
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ABSTRACT: The purpose of this study is to present a framework for quantitative analysis of spinal curvature in 3D. In order to study the properties of such complex 3D structures, we propose two descriptors that capture the characteristics of spinal curvature in 3D. The descriptors are the geometric curvature (GC) and curvature angle (CA), which are independent of the orientation and size of spine anatomy. We demonstrate the two descriptors that characterize the spinal curvature in 3D on 30 computed tomography (CT) images of normal spine and on a scoliotic spine. The descriptors are determined from 3D vertebral body lines, which are obtained by two different methods. The first method is based on the least-squares technique that approximates the manually identified vertebra centroids, while the second method searches for vertebra centroids in an automated optimization scheme, based on computer-assisted image analysis. Polynomial functions of the fourth and fifth degree were used for the description of normal and scoliotic spinal curvature in 3D, respectively. The mean distance to vertebra centroids was 1.1 mm (+/-0.6 mm) for the first and 2.1 mm (+/-1.4 mm) for the second method. The distributions of GC and CA values were obtained along the 30 images of normal spine at each vertebral level and show that maximal thoracic kyphosis (TK), thoracolumbar junction (TJ) and maximal lumbar lordosis (LL) on average occur at T3/T4, T12/L1 and L4/L5, respectively. The main advantage of GC and CA is that the measurements are independent of the orientation and size of the spine, thus allowing objective intra- and inter-subject comparisons. The positions of maximal TK, TJ and maximal LL can be easily identified by observing the GC and CA distributions at different vertebral levels. The obtained courses of the GC and CA for the scoliotic spine were compared to the distributions of GC and CA for the normal spines. The significant difference in values indicates that the descriptors of GC and CA may be used to detect and quantify scoliotic spinal curvatures. The proposed framework may therefore improve the understanding of spine anatomy and aid in the clinical quantitative evaluation of spinal deformities.
Physics in Medicine and Biology 05/2008; 53(7):1895-908. · 2.83 Impact Factor
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ABSTRACT: In this paper, we present a protocol for the evaluation of similarity measures for non-rigid registration. The evaluation is based on five intuitive properties that characterize the behavior of a similarity measure, i.e. the accuracy, capture range, distinctiveness of the optimum, number of local minima, and risk of non-convergence. These five properties are estimated locally from similarity measure values that correspond to a range of systematic local free-form deformations, obtained by displacing control points in random directions from the gold standard position. Global similarity measure properties are obtained by combining the local properties over image regions or over the entire image. The feasibility of the proposed evaluation protocol is demonstrated for three similarity measures: mutual information, normalized mutual information and correlation ratio. The evaluation is carried out on a number of MR and CT images: a pair of simulated MR T1 and MR T2 images of the head, three pairs of real MR T1 and T2 images of the head, six pairs of real MR T1 and CT images of the head, and pairs of MR and CT images of three vertebrae. The protocol may help researchers to select the most appropriate similarity measure for a non-rigid registration task.
Medical image analysis 03/2008; 12(1):42-54. · 3.09 Impact Factor
