Toward an Automatic Calibration of Dual Fluoroscopy Imaging Systems

Al-Durgham, Kaleel; Lichti, Derek D.; Kuntze, Gregor; Sharma, Gulshan B.; Ronsky, Janet L.

doi:10.5194/isprsarchives-xli-b5-757-2016

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…In this research, for determination of calibration parameters of C-arm, nineteen convergent X-ray images in both portrait and landscape orientations were captured and processed while keeping all interior parameters constant during the imaging in the pre-calibration. Moreover, in photogrammetry, having a fixed camera and a portable calibration frame is equivalent to having a fixed calibration frame and a portable camera [22,23]. Therefore, since moving the C-arm could change the intrinsic parameters of C-arm, we moved the calibration phantom to different positions with different orientations, and kept the X-ray source and the detector constant in this step.…”

Section: C-arm Calibrationmentioning

confidence: 99%

Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications

Hosseinian

Arefi

Navab

2019

Sensors

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C-arm X-ray imaging is commonly applied in operating rooms for guiding orthopedic surgeries. Augmented Reality (AR) with C-arm X-ray images during surgery is an efficient way to facilitate procedures for surgeons. However, the accurate calibration process for surgical AR based on C-arm is essential and still challenging due to the limitations of C-arm imaging systems, such as instability of C-arm calibration parameters and the narrow field of view. We extend existing methods using a depth camera and propose a new calibration procedure consisting of calibration of the C-arm imaging system, and 3D/2D calibration of an RGB-D camera and C-arm system with a new method to achieve reliable data and promising accuracy and, at the same time, consistent with standard surgical protocols. For the calibration procedure, we apply bundle adjustment equations with a 3D designed Lego multi-modal phantom, in contrast to the previous methods in which planar calibration phantoms were applied. By using our method, the visualization of the X-ray image upon the 3D data was done, and the achieved mean overlay error was 1.03 mm. The evaluations showed that the proposed calibration procedure provided promising accuracy for AR surgeries and it improved the flexibility and robustness of existing C-arm calibration methods for surgical augmented reality (using C-arm and RGB-D sensor). Moreover, the results showed the efficiency of our method to compensate for the effects of the C-arm movement on calibration parameters. It was shown that the obtained overlay error was improved for the non-zero rotation movement of C-arm by using a virtual detector.Sensors 2020, 20, 36 2 of 16 as reported in [3][4][5], and (b) AR calibration for the integration of additional sensor such as the depth camera to the C-arm.In the following, related works for C-arm surgical AR applications, and the instability of C-arm calibration parameters are explored. Then, the contributions of this study are declared. Research Overview for AR systems with C-armNavab et al.[1] proposed an AR system with video augmentation for C-arm devices in operating rooms by using mirrors. The captured X-ray images were registered with the video images by using a homography matrix. This AR system is limited to 2D guidance. For using 3D information, Habert et al. [6] applied a depth camera augmented on the C-arm by mirror construction, but this construction needed technical modifications to the C-arm device, which contradicted the minimal disruption aim [7]. It also limited the field of view and workspace of the surgeon [1,6].Habert et al. [8] and Habert [7] attached RGB-D sensors to the C-arm X-ray source and applied Zhang's method [9] with a multi-modal planar phantom in order to obtain the calibration parameters without mirrors. For calibration in the surgical AR navigation with C-arm, current studies, such as [10][11][12][13][14], have also used Zhang's method [9].In addition, there are some studies, such as [15,16], for registration of Computed Tomography (CT) data to intra-operative 3...

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Section: C-arm Calibrationmentioning

confidence: 99%

Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications

Hosseinian

Arefi

Navab

2019

Sensors

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“…In this research work, the calibration of the DF system parameters (i.e., IOPs and ROPs) is achieved using bundle adjustment with self-calibration. The details on the DF system calibration methodology using bundle adjustment can be found in (Al-Durgham et al, 2017, 2016Lichti et al, 2015). Briefly, the calibration methodology models a single X-ray source, and a single image intensifier and a single camera, as an ideal pinhole camera model (lumped system model) (Lichti et al, 2015).…”

Section: Df Imaging System and Calibration Datamentioning

confidence: 99%

Bundle Adjustment-Based Stability Analysis Method With a Case Study of a Dual Fluoroscopy Imaging System

Al-Durgham

Lichti

Detchev

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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A fundamental task in photogrammetry is the temporal stability analysis of a camera/imaging-system’s calibration parameters. This is essential to validate the repeatability of the parameters’ estimation, to detect any behavioural changes in the camera/imaging system and to ensure precise photogrammetric products. Many stability analysis methods exist in the photogrammetric literature; each one has different methodological bases, and advantages and disadvantages. This paper presents a simple and rigorous stability analysis method that can be straightforwardly implemented for a single camera or an imaging system with multiple cameras. The basic collinearity model is used to capture differences between two calibration datasets, and to establish the stability analysis methodology. Geometric simulation is used as a tool to derive image and object space scenarios. Experiments were performed on real calibration datasets from a dual fluoroscopy (DF; X-ray-based) imaging system. The calibration data consisted of hundreds of images and thousands of image observations from six temporal points over a two-day period for a precise evaluation of the DF system stability. The stability of the DF system &ndash; for a single camera analysis &ndash; was found to be within a range of 0.01 to 0.66&thinsp;mm in terms of 3D coordinates root-mean-square-error (RMSE), and 0.07 to 0.19&thinsp;mm for dual cameras analysis. It is to the authors’ best knowledge that this work is the first to address the topic of DF stability analysis.

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“…Therefore, the DLT method cannot provide the highest possible calibration and reconstruction accuracy. Bundle adjustment is a single-step, self-calibrating method which models the image distortions and the system geometry simultaneously (Lichti et al, 2015;Al-Durgham et al, 2016). A common set of IOPs and ROPs can be acquired in a multiple image calibration process using image pairs taken at different epochs.…”

Section: Introductionmentioning

confidence: 99%

“…Because of data redundancy and parameters consistency, the calibration accuracy will be improved. An automatic calibration system was proposed to reduce user intervention during the procedure (Al-Durgham et al, 2016). Preliminary data suggests that the improved bundle adjustment approach may reduce noise in the kinematic outcomes (Küpper et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

An Automatic Icp-Based 2d-3d Registration Method for a High-Speed Biplanar Videoradiography Imaging System

Zhang

Lichti

Küpper

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. High-Speed Biplanar Videoradiography (HSBV) is an X-ray based non-invasive imaging system that can be used to derive dynamic bony translations and rotations. The 2D-3D registration process matches a 3D bone model acquired from magnetic resonance imaging (MRI) or computed tomography (CT) scans with the 2D X-ray image pairs. This study focuses on the registration of MRI data as it can acquire detailed soft tissue contrast that cannot be easily discerned in CT scans. A novel 2D-3D registration method is reported in this paper that is suitable for the MRI-based bone models with high precision and high efficiency. In addition, an automatic initialization procedure with 64 starting poses is established to avoid user intervention in the registration. The method has been tested using the HSBV image sequence of a knee joint during walking. Thirty-five consecutive poses from the sequence were tested for the registration, and 50 non-consecutive poses randomly selected from the sequence were tested for the automatic initialization. The registration precision for each axis was 0.49 to 0.54 mm. For the initialization validation test, 48 over 50 frames were successfully initialized and two failed due to portions of the joint falling outside of the field-of-view of the system. The average time for each initialization is only about 6 min. The improved 2D-3D registration will allow determination of precise 3D kinematic parameters with high efficiency. These kinematic parameters can be used to calculate joint cartilage contact mechanics that provide insight into the mechanical processes and mechanisms of joint degeneration or pathology.

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Toward an Automatic Calibration of Dual Fluoroscopy Imaging Systems

Cited by 6 publications

References 10 publications

Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications

Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications

Bundle Adjustment-Based Stability Analysis Method With a Case Study of a Dual Fluoroscopy Imaging System

An Automatic Icp-Based 2d-3d Registration Method for a High-Speed Biplanar Videoradiography Imaging System

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