Marker-less real-time intra-operative camera and hand-eye calibration procedure for surgical augmented reality

Kalia M, Mathur P, Navab N, Salcudean SE (2019)


Publication Type: Journal article

Publication year: 2019

Journal

Book Volume: 6

Pages Range: 255-260

Journal Issue: 6

DOI: 10.1049/htl.2019.0094

Abstract

Accurate medical Augmented Reality (AR) rendering requires two calibrations, a camera intrinsic matrix estimation and a hand-eye transformation. We present a unified, practical, marker-less, real-time system to estimate both these transformations during surgery. For camera calibration we perform calibrations at multiple distances from the endoscope, pre-operatively, to parametrize the camera intrinsic matrix as a function of distance from the endoscope. Then, we retrieve the camera parameters intra-operatively by estimating the distance of the surgical site from the endoscope in less than 1 s. Unlike in prior work, our method does not require the endoscope to be taken out of the patient; for the hand-eye calibration, as opposed to conventional methods that require the identification of a marker, we make use of a rendered tool-tip in 3D. As the surgeon moves the instrument and observes the offset between the actual and the rendered tool-tip, they can select points of high visual error and manually bring the instrument tip to match the virtual rendered tool tip. To evaluate the hand-eye calibration, 5 subjects carried out the hand-eye calibration procedure on a da Vinci robot. Average Target Registration Error of approximately 7mm was achieved with just three data points.

Involved external institutions

How to cite

APA:

Kalia, M., Mathur, P., Navab, N., & Salcudean, S.E. (2019). Marker-less real-time intra-operative camera and hand-eye calibration procedure for surgical augmented reality. Healthcare Technology Letters, 6(6), 255-260. https://doi.org/10.1049/htl.2019.0094

MLA:

Kalia, Megha, et al. "Marker-less real-time intra-operative camera and hand-eye calibration procedure for surgical augmented reality." Healthcare Technology Letters 6.6 (2019): 255-260.

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