Relevant bibliographies by topics / Kinematic Registration

Academic literature on the topic 'Kinematic Registration'

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Published: 14 March 2023

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Journal articles on the topic "Kinematic Registration"

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Neu, C. P., R. D. McGovern, and J. J. Crisco. "Kinematic Accuracy of Three Surface Registration Methods in a Three-Dimensional Wrist Bone Study." Journal of Biomechanical Engineering 122, no. 5 (April 2, 2000): 528–33. http://dx.doi.org/10.1115/1.1289992.

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The use of registration techniques to determine motion transformations noninvasively has become more widespread with the increased availability of the necessary software. In this study, three surface registration techniques were used to generate carpal bone kinematic results from a single cadaveric wrist specimen. Surface contours were extracted from specimen computed tomography volume images of the forearm, carpal, and metacarpal bones in four arbitrary positions. Kinematic results from each of three registration techniques were compared with results derived from multiple spherical markers fixed to the specimen. Kinematic accuracy was found to depend on the registration method and bone size and shape. In general, rotation errors of the capitate and scaphoid were less than 0.5 deg for all three techniques. Rotation errors for the other bones were generally less than 2 deg, although error for the trapezoid was greater than 2 deg in one technique. Translation errors of the bones were generally less than 1 mm, although errors of the trapezoid and trapezium were greater than 1 mm for two techniques. Tradeoffs existed in each registration method between image processing time and overall kinematic accuracy. Markerless bone registration (MBR) can provide accurate measurements of carpal kinematics and can be used to study the noninvasive, three-dimensional in vivo kinematics of the wrist and other skeletal joints. [S0148-0731(00)01105-5]
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Lin, Cheng-Chung, Hsuan-Lun Lu, Tung-Wu Lu, Chia-Yang Wang, Jia-Da Li, Mei-Ying Kuo, and Horng-Chuang Hsu. "Reconstruction of Three-Dimensional Tibiofemoral Kinematics Using Single-Plane Fluoroscopy and a Personalized Kinematic Model." Applied Sciences 11, no. 20 (October 11, 2021): 9415. http://dx.doi.org/10.3390/app11209415.

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Model-based 3D/2D image registration using single-plane fluoroscopy is a common setup to determine knee joint kinematics, owing to its markerless aspect. However, the approach was subjected to lower accuracies in the determination of out-of-plane motion components. Introducing additional kinematic constraints with an appropriate anatomical representation may help ameliorate the reduced accuracy of single-plane image registration. Therefore, this study aimed to develop and evaluate a multibody model-based tracking (MbMBT) scheme, embedding a personalized kinematic model of the tibiofemoral joint for the measurement of tibiofemoral kinematics. The kinematic model was consisted of three ligaments and an articular contact mechanism. The knee joint activities in six volunteers during isolated knee flexion, lunging, and sit-to-stand motions were recorded with a biplane X-ray imaging system. The tibiofemoral kinematics determined with the MbMBT and mediolateral view fluoroscopic images were compared against those determined using biplane fluoroscopic images. The MbMBT was demonstrated to yield tibiofemoral kinematics with precision values in the range from 0.1 mm to 1.1 mm for translations and from 0.2° to 1.3° for rotations. The constraints provided by the kinematic model were shown to effectively amend the nonphysiological tibiofemoral motion and not compromise the image registration accuracy with the proposed MbMBT scheme.
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Eberharter, Johannes K., and Bahram Ravani. "Kinematic Registration in 3D Using the 2D Reuleaux Method." Journal of Mechanical Design 128, no. 2 (July 1, 2005): 349–55. http://dx.doi.org/10.1115/1.2159027.

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This paper presents a method for kinematic registration in three dimensions using a classical technique from two-dimensional kinematics, namely the Reuleaux method. In three dimensions the kinematic registration problem involves reconstruction of a spatial displacement from data on a minimum of three homologous points at two finitely separated positions of a rigid body. When more than the minimum number of homologous points are specified or when errors in specification of these points are considered, the problem becomes an over determined approximation problem. A computational geometric method is presented, resulting in a linear solution of the over determined system. The results have applications in robotics, manufacturing, and biomedical imaging. The paper considers the kinematic registration when minimal, over-determined, infinitesimal, and perturbed sets of homologous point data are given.
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Crane, Elizabeth A., Ruth B. Cassidy, Edward D. Rothman, and Geoffrey E. Gerstner. "Effect of registration on cyclical kinematic data." Journal of Biomechanics 43, no. 12 (August 2010): 2444–47. http://dx.doi.org/10.1016/j.jbiomech.2010.04.024.

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Biryukova, E. V., A. A. Frolov, I. V. Grinyagin, V. F. Korshunov, S. Yu Romanov, and I. A. Smirnitskaya. "Biomechanical Analysis of Digital Movement in Injured Hand as Method for Functional Diagnosis." N.N. Priorov Journal of Traumatology and Orthopedics 17, no. 2 (June 15, 2010): 70–77. http://dx.doi.org/10.17816/vto201017270-77.

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New method for functional diagnostics of motion activity of fingers based on registration of digital movements and their biomechanical analysis is suggested. Kinematical and dynamical parameters of digital movement accounted by biomechanical model adequately reflect the patterns of motion disorders and give the objective numerical evaluation. The method includes: a) registration of digital movement in both intact and injured hands using electromagnetic system of MiniBirds type; b) calculation of individual biomechanical parameters of fingers - length of phalanges, position and alignment; c) calculation of kinematic parameters of movement - time-base of joint angles, angular velocities and accelerations, range of motion of separate joints, degree of coordination of changes in various joints angles (kinematic synergy); d) evalua-tion of dynamic parameters of motion - time-base of total muscular forces moment in joints (dynamic synergy); e) evaluation of functional state based on analysis of kinematic and dynamic parameters of motion before, during and after treatment.
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Beek, Maarten, Carolyn F. Small, Randy E. Ellis, Richard W. Sellens, and David R. Pichora. "Bone Alignment Using the Iterative Closest Point Algorithm." Journal of Applied Biomechanics 26, no. 4 (November 2010): 526–30. http://dx.doi.org/10.1123/jab.26.4.526.

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Computer assisted surgical interventions and research in joint kinematics rely heavily on the accurate registration of three-dimensional bone surface models reconstructed from various imaging technologies. Anomalous results were seen in a kinematic study of carpal bones using a principal axes alignment approach for the registration. The study was repeated using an iterative closest point algorithm, which is more accurate, but also more demanding to apply. The principal axes method showed errors between 0.35 mm and 0.49 mm for the scaphoid, and between 0.40 mm and 1.22 mm for the pisiform. The iterative closest point method produced errors of less than 0.4 mm. These results show that while the principal axes method approached the accuracy of the iterative closest point algorithm in asymmetrical bones, there were more pronounced errors in bones with some symmetry. Principal axes registration for carpal bones should be avoided.
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Nederbragt, Walter W., and Bahram Ravani. "Enumeration of Contact Geometries for Kinematic Registration Using Tactile Sensing Fixtures." Journal of Mechanical Design 128, no. 1 (May 5, 2005): 34–45. http://dx.doi.org/10.1115/1.2118731.

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This paper uses group theory for enumeration of contacts between geometric elements necessary for kinematic registration or part referencing in robotics. The results are applied to type synthesis of tactile sensing mechanical fixtures. Kinematic registration is an important step in robot calibration and in data driven automation. Although the scope of the paper is limited to geometric contacts involving points, lines, planar surfaces, cylindrical surfaces, and spherical surfaces, the techniques developed are general and can be applied to other geometric features and non-tactile sensing elements used in robotic calibration and part referencing.
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Hinz, Lennart, Markus Kästner, and Eduard Reithmeier. "Metal Forming Tool Monitoring Based on a 3D Measuring Endoscope Using CAD Assisted Registration." Sensors 19, no. 9 (May 5, 2019): 2084. http://dx.doi.org/10.3390/s19092084.

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In order to provide timely, reliable, and comprehensive data for the maintenance of highly stressed geometries in sheet-bulk metal forming tools, this article features a possible setup by combining a 3D measuring endoscope with a two-stage kinematic. The measurement principle is based on the projection of structured light, allowing time-effective measurements of larger areas. To obtain data of proper quality, several hundred measurements are performed which then have to be registered and finally merged into one single point cloud. Factors such as heavy, unwieldy specimens affecting precise alignment. The rotational axes are therefore possibly misaligned and the kinematics and the hand-eye transformation remain uncalibrated. By the use of computer-aided design (CAD) data, registration can be improved, allowing a detailed examination of local features like gear geometries while reducing the sensitivity to detect shape deviations.
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Lopomo, Nicola, Francesca Colle, Cecilia Signorelli, Marco Bontempi, Matteo Baracchi, and Andrea Visani. "ONE-STEP FUNCTIONAL REGISTRATION FOR KINEMATIC ANALYSIS IN COMPUTER AIDED SURGERY." Journal of Biomechanics 45 (July 2012): S65. http://dx.doi.org/10.1016/s0021-9290(12)70066-0.

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Wieckiewicz, Mieszko, Marek Zietek, Danuta Nowakowska, and Wlodzimierz Wieckiewicz. "Comparison of Selected Kinematic Facebows Applied to Mandibular Tracing." BioMed Research International 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/818694.

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The study focused on the comparison between mechanical and computerized registration methods used by the two selected kinematic facebows. The material consisted of 35 women aged 18 to 35, studied using the Gerber Dynamic Facebow and the computerized ARCUSdigma II axiograph. To compare the devices the condylar path inclination (CPI) was recorded according to the Camper’s line, enabling the acquisition of easily comparable values based on which the devices were objectively and subjectively analyzed. Statistics was performed for the obtained data. The study showed that the values for the CPI registrated by the ARCUSdigma II are significantly higher than those obtained by using the Gerber Dynamic Facebow. The significant difference in the records of the CPI is most likely a result of the differences in the registration techniques assumptions. ARCUSdigma II provides the user with more diagnostic options than Gerber Dynamic Facebow. Mechanical facebow handling has a higher risk of hand-measuring errors in tracing procedure. Due to high discrepancy of achieved results from different systems the authors recommend to use articulator compatible with facebow whose measurement has been done.
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Dissertations / Theses on the topic "Kinematic Registration"

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Garetier, Marc. "Développement et application de l'IRM dynamique dans le domaine musculo-squelettique In vivo ankle joint kinematics from dynamic magnetic resonance imaging using a registration-based framework, in Journal of Biomechanics 86, March 2019 Dynamic MRI for articulating joint evaluation on 1.5T and 3.0T scanners : Setup, protocols, and real-time sequences, in Insights Into Imaging, 2020." Thesis, Brest, 2020. http://www.theses.fr/2020BRES0023.

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Les troubles de l’appareil musculosquelettiques retentissent sur le mouvement avec un impact parfois important sur la qualité de vie.L’IRM dynamique est une technique d’imagerie qui peut être employée pour l’évaluation non invasive in vivo de cet appareil en mouvement. Elle regroupe trois principales méthodes, dont l’imagerie temps réel qui permet la visualisation d’images acquises de manière rapide et continue. L’IRM temps réel est basée sur des séquences d’écho de gradient rapide, en particulier les séquences avec destruction de l’aimantation transversale résiduelle et celles avec gradients équilibrés. Ces séquences permettent de concilier une résolution temporelle élevée et une qualité d’image suffisante pour l’analyse des données, avec cependant des limites inhérentes à leurs caractéristiques. L’IRM dynamique a été utilisée dans plusieurs applications musculo-squelettiques, participant ainsi à une meilleure compréhension de la biomécanique et de la pathologie, avec comme objectif une amélioration de la prise en charge des patients. Les paramètres biomécaniques estimés au niveau du doigt par IRM dynamique temps réel sont proches de ceux rapportés dans la littérature, comme le bras de levier ou la course du tendon. Cette technique d’imagerie peut également être employée pour évaluer la contraction du muscle par quantification sa déformation. L’intégration de cette technique d’imagerie dans la pratique clinique nécessite par contre une standardisation des paramètres des séquences utilisées et une connaissance de l’installation appropriée du patient et des antennes
Musculoskeletal disorders affect the movement of the body, with a significant impact on quality of life. Dynamic MRI allows for the non-invasive and invivo evaluation of musculoskeletal system during motion. Dynamic MRI can be acquired by three main methods, including real-time imaging allowing rapid and continuous image acquisition. Real-time dynamic MRI is based on rapid gradient echo sequences, in particularly spoiled gradient echo sequence and balanced steady state free precession sequence. These sequences provide high temporal resolution and sufficient image quality for data analysis, but with their own limitations. Dynamic MRI has been used for many musculoskeletal applications, allowing to better understand biomechanics and diseases, inorder to improve patient management. The finger biomechanical parameters obtained with real-time dynamic MRI are close to those reported in the literature, as tendon excursion or moment arm. This technique can also be used to assess muscle contraction by quantifying muscle deformation. Clinical implementation of this imaging modality requires also standardization of the sequence parameters and knowledge of the suitable patient and coil installation
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Book chapters on the topic "Kinematic Registration"

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Dooley, John R. "Kinematic Registration." In Encyclopedia of Robotics, 1–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-642-41610-1_140-1.

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Hamadeh, Ali, and Philippe Cinquin. "Kinematic study of lumbar spine using functional radiographies and 3D / 2D registration." In Lecture Notes in Computer Science, 109–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0029230.

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Ramalhinho, João, Henry Tregidgo, Moustafa Allam, Nikolina Travlou, Kurinchi Gurusamy, Brian Davidson, David Hawkes, Dean Barratt, and Matthew J. Clarkson. "Registration of Untracked 2D Laparoscopic Ultrasound Liver Images to CT Using Content-Based Retrieval and Kinematic Priors." In Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis, 11–19. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32875-7_2.

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Yamazaki, Takaharu, Yuichi Hayashi, Tetsuya Tomita, Kenichi Kono, Yoshinobu Sato, and Kazuomi Sugamoto. "Basic Study for 3D Kinematic Measurement of Patella from Single-Plane Fluoroscopic Image Using Intensity-Based 2D/3D Registration." In IFMBE Proceedings, 767–71. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-9038-7_142.

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Yamazaki, T., Y. Nagamoto, H. Sakaura, D. Maeda, H. Yoshikawa, and K. Sugamoto. "3D Spine Kinematics on Riding Fitness Machines Using 2D/3D Image Registration." In IFMBE Proceedings, 222–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-29305-4_60.

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Yang, L., J. Wang, H. Liao, H. Yamashita, I. Sakuma, T. Chiba, and E. Kobayashi. "Self-registration of Ultrasound Imaging Device to Navigation System Using Surgical Instrument Kinematics in Minimally Invasive Procedure." In Computer Aided Surgery, 95–103. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-55810-1_8.

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Crisco, Joseph J., Robert D. McGovern, and Scott W. Wolfe. "Three-dimensional joit kinematics using bone surface registration: A computer assisted approach with an application to the wrist joint in vivo." In Medical Image Computing and Computer-Assisted Intervention — MICCAI’98, 696–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0056256.

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"- Pulmonary Kinematics via Registration of Serial Lung Images." In Lung Imaging and Computer Aided Diagnosis, 122–49. CRC Press, 2016. http://dx.doi.org/10.1201/b11106-9.

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Conference papers on the topic "Kinematic Registration"

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Eberharter, Johannes K., and Bahram Ravani. "Kinematic Registration Using Line Geometry." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57549.

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This paper uses line geometry to find an elegant solution to the kinematic registration problem involving reconstruction of a spatial displacement from data on three homologous points at two finitely separated positions of a rigid body. The bisecting linear line complex of two position theory in kinematics is used in combination with recent results from computational line geometry to present an elegant computational geometric method for the solution of this old problem. The results have applications in robotics, manufacturing, and biomedical imaging. The paper considers when minimal, over-determined, and perturbed sets of point data are given.
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Marchelli, Grant L. S., David R. Haynor, William R. Ledoux, Mark A. Ganter, and Duane W. Storti. "Graphical User Interface for Human Intervention in 2D-3D Registration of Medical Images." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13659.

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Image-guided medical therapies and image-guided biomechanical measurement systems often combine 2D and 3D imaging modalities. Determination of relations between the 2D and 3D imaging data is known as 2D-3D registration. Motivated by an ongoing project aimed at non-invasive, marker-free measurement of the kinematics of the bones in the foot during gait, we consider a registration approach that involves (1) computing projections of the 3D data set, (2) computing a quality measure to describe the agreement/discrepancy between the simulated projections and actual 2D images, and (3) optimization of the quality measure relative to the kinematic degrees of freedom to determine the optimal registration. For our particular project, the 3D imaging modality is CT scan, the 2D modality is bi-plane fluoroscopy, the computed projection is a digitally reconstructed radiograph (DRR), the quality measure is normalized cross-correlation (NCC) between a pair of DRRs and a pair of corresponding fluoroscope images, and the 2D imaging includes a sequence of several hundred stereo image pairs. We have recently released a software toolkit, DRRACC, that accelerates both the DRR and NCC computations via GPU-based parallel processing to enable more efficient automated determination of kinematic relations for optimal registration. While fully automated 2D-3D registration is desirable, there are situations (such as creating a reasonable starting configuration for optimization, re-starting after the optimizer fails to converge, and visual verification of registration relations) when it is desirable/necessary to have a human in the loop. In this paper, we present an OpenGL-based graphical user interface that employs the DRRACC toolkit to allow the user to manipulate the kinematics of individual objects (bones) segmented from the 3D imaging and to view the corresponding DRR and the associated correlation with a reference image in real time. We also present plots showing initial results for the dependence of the registration measure on pairs of kinematic parameters. The plots show well-defined peaks that support the hope for automated registration, but they also contain large relatively flat regions that may prove problematic for gradient-based optimizers and necessitate the sort of interface presented in this paper.
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Nederbragt, Walter W., and Bahram Ravani. "Enumeration of Contact Geometries for Kinematic Registration Using Tactile Sensing Fixtures." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASME, 2002. http://dx.doi.org/10.1115/detc2002/mech-34324.

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Li, Meng, Qinghua Huang, Wenrui Li, and Jianyi Li. "CT to ultrasound registration for non-invasive kinematic analysis of knee joints." In 2017 4th International Conference on Systems and Informatics (ICSAI). IEEE, 2017. http://dx.doi.org/10.1109/icsai.2017.8248467.

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Ma, Zhen, and He Xu. "A Kinematic-Based Unmarked Augmented Reality Method for Large Scene Industrial Workshops." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23827.

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Abstract In the present study, a mobile camera positioning method based on kinematics of robot is proposed, capable of achieving far point positioning of imaging position and attitude tracking in large-scene enhancement. Orbit precision motion via the framework overhead cameras and combined with the ground system of sensor array object (e.g., mobile robot platform of various sensors) is capable of achieving the effective 3D image registration, solving any artifact that refers to a mobile robot in large-space position initialization, as well as effectively implementing the large-space no marks augmented reality, human-computer interaction and information summary. Lastly, the feasibility of the method is verified experimentally.
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Biondi, Gabriele, Stefano Mauro, and Stefano Pastorelli. "Kinematic registration and shape analysis for locating center of mass in large passive spacecraft." In 2017 IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace). IEEE, 2017. http://dx.doi.org/10.1109/metroaerospace.2017.7999537.

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Pickering, Mark R., Jennie M. Scarvell, and Paul N. Smith. "An improved CT to fluoroscopy registration algorithm for the kinematic analysis of knee joints." In 2009 16th International Conference on Digital Signal Processing (DSP). IEEE, 2009. http://dx.doi.org/10.1109/icdsp.2009.5201122.

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Jerbi, T., V. Burdin, E. Stindel, and C. Roux. "A 2D 3D registration with low dose radiographic system for in vivo kinematic studies." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6091990.

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Akter, Masuma, Andrew J. Lambert, Mark R. Pickering, Jennie M. Scarvell, and Paul N. Smith. "A 2D-3D Image Registration Algorithm Using Log-Polar Transforms for Knee Kinematic Analysis." In 2012 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2012. http://dx.doi.org/10.1109/dicta.2012.6411731.

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Conrad, Bryan P., and Scott A. Banks. "Measurement of 3D Vertebral Body Position and Orientation Using Single Plane Fluoroscopy." In ASME 2010 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2010. http://dx.doi.org/10.1115/sbc2010-19697.

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The increasing use of motion preserving devices in the spine has highlighted the need for accurate kinematic measurement tools to evaluate the performance of these new implants. In addition to quantifying the motion of the implant itself, it is also desirable to measure how implants affect the motion at adjacent vertebral levels. Single plane fluoroscopy has been used for over 15 years to analyze the in vivo motions of total knee replacement implants, with reported accuracies of 0.5–1.0 deg for rotations and 0.5 mm for in plane translations1,2. It is our goal to apply this type of image registration technique to the spine, so that accurate 3D kinematics of vertebral motion can be measured in vivo. This involves a significant extension to previous work, instead of tracking silhouettes of implants, we proposed to use digitally reconstructed radiograph images generated from a CT as the basis for image registration. The purpose of this project was to develop a methodology that would enable the 3D position and orientation (pose) of a vertebral body to be accurately measured from a single plane fluoroscopic image.
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