Toward an Automatic Calibration of Dual Fluoroscopy Imaging Systems (original) (raw)
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X-ray imaging is a fundamental tool of routine clinical diagnosis. Fluoroscopic imaging can further acquire X-ray images at video frame rates, thus enabling non-invasive in-vivo motion studies of joints, gastrointestinal tract, etc. For both the qualitative and quantitative analysis of static and dynamic X-ray images, the data should be free of systematic biases. Besides precise fabrication of hardware, software-based calibration solutions are commonly used for modelling the distortions. In this primary research study, a robust photogrammetric bundle adjustment was used to model the projective geometry of two fluoroscopic X-ray imaging systems. However, instead of relying on an expert photogrammetrist's knowledge and judgement to decide on a parametric model for describing the systematic errors, a self-tuning data-driven approach is used to model the complex non-linear distortion profile of the sensors. Quality control from the experiment showed that 0.06 mm to 0.09 mm 3D reconstruction accuracy was achievable post-calibration using merely 15 X-ray images. As part of the bundle adjustment, the location of the virtual fluoroscopic system relative to the target field can also be spatially resected with an RMSE between 3.10 mm and 3.31 mm.
Image-Based Matching for Natural Knee Kinematics Measurement Using Single-Plane Fluoroscopy
Journal of the Japanese Society for Experimental Mechanics, 2009
The purpose of the present study is to develop a direct and accurate method for measuring knee kinematics by using single-plane fluoroscopy. The 3-dimensional (3D) position of the bone (in other words, the 6 degree-of-freedom (DOF) parameters) was recovered by matching the digitally reconstructed radiographs (DRRs) generated from the 3D volume model of the bone on the basis of the fluoroscopic image. The root-mean-square error (RMSE) of the overall rotation parameters was within 2.1 degrees. For the translation parameters RMSE took its maximal value of 3.6 mm in the out-of-plane direction. This indicates that the present method has potential for clinical application.
Medical engineering & physics, 2018
Biplane 2D-3D model-based registration and radiostereometric analysis (RSA) approaches have been commonly used for measuring three-dimensional, in vivo joint kinematics. However, in clinical biplane systems, the x-ray images are acquired asynchronously, which introduces registration errors. The present study introduces an interpolation technique to reduce image registration error by generating synchronous fluoroscopy image estimates. A phantom study and cadaveric shoulder study were used to evaluate the level of improvement in image registration that could be obtained as a result of using our interpolation technique. Our phantom study results show that the interpolated bead tracking technique was in better agreement with the true bead positions than when asynchronous images were used alone. The overall RMS error of glenohumeral kinematics for interpolated biplane registration was reduced by 1.27 mm, 0.40 mm, and 0.47 mm in anterior-posterior, superior-inferior, and medial-lateral tr...
Photogrammetric Modelling for 3D Reconstruction from a Dual Fluoroscopic Imaging System
2019
Biplanar videoradiography (BPVR), or clinically referred to as dual fluoroscopy (DF), imaging systems are increasingly being used to study the in-vivo skeletal biomechanics of human and animal locomotion. DF imaging provides a novel solution to quantify the six-degree-of-freedom (6DOF) skeletal kinematics of humans and animals with high accuracy and temporal resolution. Using low-dose X-ray radiation, DF systems provide accurate bone rotation and translation measurements. In this research domain, a DF system comprises two X-ray sources, two image intensifiers and two high-speed video cameras. The combination of these elements allows for the stereoscopic imaging of the bones of a joint at high temporal resolution (e.g., 120-250 Hz), from which bone kinematics can be estimated. The utilization of X-ray-based imaging results in challenges that are uncommon in optical photogrammetry. Unlike optical images, the inherent lack of colour information in DF images complicates fundamental task...
Robust automatic C-arm calibration for fluoroscopy-based navigation: a practical approach
2002
This paper presents a new on-line automatic X-ray fluoroscopic C-arm calibration method for intraoperative use. C-arm calibration is an essential prerequisite for accurate X-ray fluoroscopy-based navigation and image-based registration. Our method utilizes a customdesigned calibration ring with a two-plane pattern of fiducials that attaches to the C-arm image intensifier, and an on-line calibration algorithm. The algorithm is robust, fully automatic, and works with images containing anatomy and surgical instruments which cause fiducial occlusions. It consists of three steps: fiducial localization, distortion correction, and camera calibration. Our experimental results show submillimetric accuracy for calibration and tip localization with occluded fiducials.
Simultaneous Two-View Calibration of Biplane Fluoroscopic Imaging Systems
Abstract. We present a novel method for calibrating biplane fluoroscopy systems using sequences of paired views. This method uses standard techniques to estimate the system calibration on a frame-by-frame basis, then uses a global parameter optimization (bundle adjustment) to improve the quality and consistency of the solution. The method is validated using images of a new calibration phantom.
3D Elbow Kinematics with Monoplanar Fluoroscopy
Eurasip Journal on Advances in Signal Processing, 2010
An in-silico assessment of the performance of 3D video-fluoroscopy for the analysis of the kinematics of long bones is proposed. A reliable knowledge of in-vivo joints kinematics in physiological conditions is fundamental in the clinical field. 3D videofluoroscopy theoretically permits a mm/deg level of accuracy in joint motion analysis, but the optimization algorithm for the pose estimation is highly dependent on the geometry of the bone segment analyzed. An automated technique based on distance maps and tangency condition was applied to the elbow bones. The convergence domain was explored to quantify and optimize measurement accuracy in terms of bias and precision. By conditioning the optimization algorithm using simple image features, the estimation error had small dispersion (interquartile range within 0.5 and 0.025 mm/deg for out-of-plane and in-plane pose parameters, resp.), but with occasional bias and outliers. 3D video-fluoroscopy produced promising results for the elbow joint, but further in-vitro validation studies should be carried out.
A Fast and Robust Framework for 3D/2D Model to Multi-frame Fluoroscopy Registration
IEEE Access, 2021
Three-dimensional (3D) kinematic analysis plays an important role in improving diagnosis and in the evaluation of treatments and surgical procedures. For example, measuring the 3D kinematics of knee joints is essential for understanding their normal function and diagnosing any pathology, such as ligament injury and osteoarthritis. Image registration is a method which can be used to compute kinematic measurements without involving the introduction of instruments into the body. However, in these techniques, the trade-off between accuracy and computation time is still a challenging problem which needs to be addressed. In this paper, a fast and robust registration method is proposed for the measurement of postoperative knee joint kinematics. Using this method, after total knee arthroplasty (TKA) surgery, a 3D knee implant model can be registered with a number of single-plane fluoroscopy frames of the patients' knee. Generally, when the number of fluoroscopy frames is quite high, the computation cost for the registration between the frames and a 3D model is expensive. Therefore, in order to speed up the registration process, we apply an interpolation-based prediction method, to initialize and estimate the 3D positions of the 3D model in each fluoroscopy frame. The estimated 3D positions are then fine-tuned. The experimental results, which were performed on the knee joints of 18 patients post surgery, show that the computational time required to register each frame for each bone using our proposed method is only 67 seconds, which is much faster (almost 6.5 times faster) than the best existing registration method (a registration method based on sum of conditional variance (SCV) similarity measure) while maintaining almost the same accuracy. The average of the mean difference +/-standard deviation of the proposed method for femoral and tibial bones for translation and rotation parameters are 0.0603 +/-0.2966 (mm) and-0.0069 +/-0.2922 (degree) respectively.
2D-3D Registration of CT Vertebra Volume to Fluoroscopy Projection: A Calibration Model Assessment
Eurasip Journal on Advances in Signal Processing, 2010
This study extends a previous research concerning intervertebral motion registration by means of 2D dynamic fluoroscopy to obtain a more comprehensive 3D description of vertebral kinematics. The problem of estimating the 3D rigid pose of a CT volume of a vertebra from its 2D X-ray fluoroscopy projection is addressed. 2D-3D registration is obtained maximising a measure of similarity between Digitally Reconstructed Radiographs (obtained from the CT volume) and real fluoroscopic projection. X-ray energy correction was performed. To assess the method a calibration model was realised a sheep dry vertebra was rigidly fixed to a frame of reference including metallic markers. Accurate measurement of 3D orientation was obtained via single-camera calibration of the markers and held as true 3D vertebra position; then, vertebra 3D pose was estimated and results compared. Error analysis revealed accuracy of the order of 0.1 degree for the rotation angles of about 1 mm for displacements parallel to the fluoroscopic plane, and of order of 10 mm for the orthogonal displacement.
3D elbow kinematics with monoplanar fluoroscopy: in silico evaluation
EURASIP Journal on Advances in …, 2010
An in-silico assessment of the performance of 3D video-fluoroscopy for the analysis of the kinematics of long bones is proposed. A reliable knowledge of in-vivo joints kinematics in physiological conditions is fundamental in the clinical field. 3D videofluoroscopy theoretically permits a mm/deg level of accuracy in joint motion analysis, but the optimization algorithm for the pose estimation is highly dependent on the geometry of the bone segment analyzed. An automated technique based on distance maps and tangency condition was applied to the elbow bones. The convergence domain was explored to quantify and optimize measurement accuracy in terms of bias and precision. By conditioning the optimization algorithm using simple image features, the estimation error had small dispersion (interquartile range within 0.5 and 0.025 mm/deg for out-of-plane and in-plane pose parameters, resp.), but with occasional bias and outliers. 3D video-fluoroscopy produced promising results for the elbow joint, but further in-vitro validation studies should be carried out.