Light modelling and calibration in laparoscopy
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ORIGINAL ARTICLE
Light modelling and calibration in laparoscopy Richard Modrzejewski1,3 · Toby Collins2,3 · Alexandre Hostettler2,3 · Jacques Marescaux2,3 · Adrien Bartoli1 Received: 16 November 2019 / Accepted: 3 April 2020 © CARS 2020
Abstract Purpose A better understanding of photometry in laparoscopic images can increase the reliability of computer-assisted surgery applications. Photometry requires modelling illumination, tissue reflectance and camera response. There exists a large variety of light models, but no systematic and reproducible evaluation. We present a review of light models in laparoscopic surgery, a unified calibration approach, an evaluation methodology, and a practical use of photometry. Method We use images of a calibration checkerboard to calibrate the light models. We then use these models in a proposed dense stereo algorithm exploiting the shading and simultaneously extracting the tissue albedo, which we call dense shading stereo. The approach works with a broad range of light models, giving us a way to test their respective merits. Results We show that overly complex light models are usually not needed and that the light source position must be calibrated. We also show that dense shading stereo outperforms existing methods, in terms of both geometric and photometric errors, and achieves sub-millimeter accuracy. Conclusion This work demonstrates the importance of careful light modelling and calibration for computer-assisted surgical applications. It gives guidelines on choosing the best performing light model. Keywords Light modelling · Surface reconstruction · Densification method · Multi view stereo
Introduction: clinical motivation and existing works Augmented reality (AR) in laparoscopic surgery is a major task, widely studied over the last decade [3,5,6,10]. Nevertheless, while AR is solved in some non-medical applications, laparoscopic surgery lags behind because of complicating factors such as lack of texture, strong deformations and illumination changes. The general AR pipeline for laparoscopy has five main stages [6]: (1) preoperative organ Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11548-020-02161-8) contains supplementary material, which is available to authorized users.
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Richard Modrzejewski [email protected] Toby Collins [email protected]
1
EnCoV, Institut Pascal, UMR 6602, CNRS/UBP/SIGMA, EnCoV, 63000 Clermont-Ferrand, France
2
IRCAD, 1 Place de l’Hopital, 67000 Strasbourg, France
3
IHU Strasbourg, 1 Place de l’Hôpital, 67091 Strasbourg, France
model reconstruction from volumetric data, (2) intraoperative 3D organ reconstruction, (3) reconstruction scale estimation (4) deformable registration and model texturing, and (5) deformation tracking. Photometric cues may be used to overcome the previously described difficulties, at all stages except (1). For the sake of clarity, we here focus on stage (2). The intra-operative 3D organ reconstruction is computed from an exploration video captured at the begi
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