An on-board surgical tracking and video augmentation system for C-arm image guidance

Reaungamornrat, S.; Otake, Yoshito; Uneri, Ali; Schäfer, Sebastian; Mirota, Daniel; Nithiananthan, Sajendra; Stayman, J. Webster; Kleinszig, Gerhard; Khanna, A. Jay; Taylor, Russell H.; Siewerdsen, J. H.

doi:10.1007/s11548-012-0682-9

Cited by 32 publications

(19 citation statements)

References 44 publications

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“…As a result of the calibration, they utilized the hexagonal reference marker to track the gantry during rotation and maintain registration for DRR generation, surgical tracking and video augmentation. 9 Albiol et al calibrated an RGB camera to a conventional diagnostic X-Ray system to identify equivalent points of interest in both modalities using Epipolar geometry. The method enables measurements of real anatomic lengths and angles.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The above described solutions for calibration use optical axis alignment together with a 2D homography estimation, marker based registration, 3,8 CBCT acquisition with calibration phantoms, 9,11 or hand-eye calibration with the acquisition of up to 160 pose pairs. 15 All presented systems establish correspondences between the two modalities, the attached sensor and the C-arm imaging device by acquiring color and/or depth images and X-Ray or CBCT scans, thus emitting radiation.…”

Section: Radiation Free Calibration By Analyzing the Geometrymentioning

confidence: 99%

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Pivot calibration concept for sensor attached mobile c-arms

Lee

Seibold

Fürnstahl

et al. 2020

Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling

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Medical augmented reality has been actively studied for decades and many methods have been proposed to revolutionize clinical procedures. One example is the camera augmented mobile C-arm (CAMC), which provides a real-time video augmentation onto medical images by rigidly mounting and calibrating a camera to the imaging device. Since then, several CAMC variations have been suggested by calibrating 2D/3D cameras, trackers, and more recently a Microsoft HoloLens to the C-arm. Different calibration methods have been applied to establish the correspondence between the rigidly attached sensor and the imaging device. A crucial step for these methods is the acquisition of X-Ray images or 3D reconstruction volumes; therefore, requiring the emission of ionizing radiation. In this work, we analyze the mechanical motion of the device and propose an alternatative method to calibrate sensors to the C-arm without emitting any radiation. Given a sensor is rigidly attached to the device, we introduce an extended pivot calibration concept to compute the fixed translation from the sensor to the C-arm rotation center. The fixed relationship between the sensor and rotation center can be formulated as a pivot calibration problem with the pivot point moving on a locus. Our method exploits the rigid C-arm motion describing a Torus surface to solve this calibration problem. We explain the geometry of the C-arm motion and its relation to the attached sensor, propose a calibration algorithm and show its robustness against noise, as well as trajectory and observed pose density by computer simulations. We discuss this geometric-based formulation and its potential extensions to different C-arm applications.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Radiation Free Calibration By Analyzing the Geometrymentioning

confidence: 99%

Pivot calibration concept for sensor attached mobile c-arms

Lee

Seibold

Fürnstahl

et al. 2020

Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling

View full text Add to dashboard Cite

show abstract

“…However this approach was not grounded on a formal model and addresses calibration or motion inaccuracies in an ad hoc fashion. Practical cross-calibration of a RGB(D) system with X-rays has been addressed in a number of previous works using 2D objects such as a visible checker-board with X-ray opaque balls [24] or a metal sheet checker-board [8], as well as 3D objects such as markers on a 3D cylinder [25], 3D rings and spheres [26], or a hex-faced marker [27].…”

Section: Related Workmentioning

confidence: 99%

CBCT of a Moving Sample From X-Rays and Multiple Videos

Pansiot

Boyer

2019

IEEE Trans. Med. Imaging

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In this paper we consider dense volumetric modeling of moving samples such as body parts. Most dense modeling methods consider samples observed with a moving X-ray device and cannot easily handle moving samples. We propose instead a novel method to observe shape motion from a fixed X-ray device and to build dense in-depth attenuation information. This yields a low-cost, low-dose 3D imaging solution, taking benefit of equipment widely available in clinical environments. Our first innovation is to combine a video-based surface motion capture system with a single low-cost/low-dose fixed planar X-ray device, in order to retrieve the sample motion and attenuation information with minimal radiation exposure. Our second innovation is to rely on Bayesian inference to solve for a dense attenuation volume given planar radioscopic images of a moving sample. This approach enables multiple sources of noise to be considered and takes advantage of very limited prior information to solve an otherwise ill-posed problem. Results show that the proposed strategy is able to reconstruct dense volumetric attenuation models from a very limited number of radiographic views over time on synthetic and in-situ data.

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“…Binocular visual navigation is a visual tracking system to explore the orientation of a target template using visible light with two cameras, similar to human eyes . The tracker scans a specific marker with alternating black and white and calculates the angles and distances via computer according to the designed regulations. The tracking system presents a real‐time position and posture change of the target template.…”

Section: Introductionmentioning

confidence: 99%

Application of binocular visual navigation technique in diaphyseal fracture reduction

Hao

et al. 2020

Robotics Computer Surgery

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Background: Computer-assisted surgical navigation techniques have shown promise; however, currently popular systems have limitations. This paper presents the characterization and application of a binocular visual navigation technique in diaphyseal fracture reduction.Methods: A binocular visual tracker (MicronTracker) was introduced to reduce diaphyseal fractures. A transformation matrix was used to acquire the reduction parameters. A transverse diaphyseal fracture was used as a control group.Results: Precision tests were performed with the binocular system using a simulation femoral model with a transverse fracture 12 times. All residual deformations were compared and P < 0.01. Conclusions:The binocular visual navigation technique produces good results with advantages of flexibility and high positional accuracy and shows promise. The Micro-nTracker might lead to further application in the remote navigation field.

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An on-board surgical tracking and video augmentation system for C-arm image guidance

Cited by 32 publications

References 44 publications

Pivot calibration concept for sensor attached mobile c-arms

Pivot calibration concept for sensor attached mobile c-arms

CBCT of a Moving Sample From X-Rays and Multiple Videos

Application of binocular visual navigation technique in diaphyseal fracture reduction

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