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Pivot calibration concept for sensor attached mobile c-arms


Lee, Sing Chun; Seibold, Matthias; Fürnstahl, Philipp; Farshad, Mazda; Navab, Nassir (2020). Pivot calibration concept for sensor attached mobile c-arms. In: Image-Guided Procedures, Robotic Interventions, and Modeling, Houston, United States, 15 February 2020 - 20 February 2020.

Abstract

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 alternative 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.

Abstract

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 alternative 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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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Electronic, Optical and Magnetic Materials
Physical Sciences > Condensed Matter Physics
Physical Sciences > Computer Science Applications
Physical Sciences > Applied Mathematics
Physical Sciences > Electrical and Electronic Engineering
Language:English
Event End Date:20 February 2020
Deposited On:08 Feb 2021 15:39
Last Modified:09 Feb 2021 21:05
Publisher:SPIE
ISBN:9781510633971
OA Status:Green
Publisher DOI:https://doi.org/10.1117/12.2547581

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