no code implementations • 25 Mar 2024 • Jonas Hein, Frederic Giraud, Lilian Calvet, Alexander Schwarz, Nicola Alessandro Cavalcanti, Sergey Prokudin, Mazda Farshad, Siyu Tang, Marc Pollefeys, Fabio Carrillo, Philipp Fürnstahl
In this paper, we present a proof of concept (PoC) for surgery digitalization that is applied to an ex-vivo spinal surgery performed in realistic conditions.
no code implementations • 29 Jan 2024 • Sascha Jecklin, Youyang Shen, Amandine Gout, Daniel Suter, Lilian Calvet, Lukas Zingg, Jennifer Straub, Nicola Alessandro Cavalcanti, Mazda Farshad, Philipp Fürnstahl, Hooman Esfandiari
Recently, our work X23D showed an approach for generating 3D anatomical models of the spine from only a few intraoperative fluoroscopic images.
no code implementations • 5 Aug 2023 • Florentin Liebmann, Marco von Atzigen, Dominik Stütz, Julian Wolf, Lukas Zingg, Daniel Suter, Laura Leoty, Hooman Esfandiari, Jess G. Snedeker, Martin R. Oswald, Marc Pollefeys, Mazda Farshad, Philipp Fürnstahl
An intuitive surgical guidance is provided thanks to the integration into an augmented reality based navigation system.
no code implementations • 9 May 2023 • Yunke Ao, Hooman Esfandiari, Fabio Carrillo, Yarden As, Mazda Farshad, Benjamin F. Grewe, Andreas Krause, Philipp Fuernstahl
Spinal fusion surgery requires highly accurate implantation of pedicle screw implants, which must be conducted in critical proximity to vital structures with a limited view of anatomy.
no code implementations • 5 May 2023 • Jonas Hein, Nicola Cavalcanti, Daniel Suter, Lukas Zingg, Fabio Carrillo, Lilian Calvet, Mazda Farshad, Marc Pollefeys, Nassir Navab, Philipp Fürnstahl
Third, we evaluate three state-of-the-art single-view and multi-view methods for the task of 6DoF pose estimation of surgical instruments and analyze the influence of camera configurations, training data, and occlusions on the pose accuracy and generalization ability.
no code implementations • 27 Mar 2023 • Aidana Massalimova, Maikel Timmermans, Nicola Cavalcanti, Daniel Suter, Matthias Seibold, Fabio Carrillo, Christoph J. Laux, Reto Sutter, Mazda Farshad, Kathleen Denis, Philipp Fürnstahl
The best-performing data fusion model combined the latter two sensors with a breach recall of 98\%.
no code implementations • 5 Nov 2022 • Mane Margaryan, Matthias Seibold, Indu Joshi, Mazda Farshad, Philipp Fürnstahl, Nassir Navab
In contrast to previously proposed fully convolutional models, the proposed model implements residual Squeeze and Excitation modules in the generator architecture.
no code implementations • 22 Mar 2022 • Matthias Seibold, Armando Hoch, Mazda Farshad, Nassir Navab, Philipp Fürnstahl
In this work, we propose a novel data augmentation method for clinical audio datasets based on a conditional Wasserstein Generative Adversarial Network with Gradient Penalty (cWGAN-GP), operating on log-mel spectrograms.
no code implementations • 17 Jan 2020 • Florentin Liebmann, Simon Roner, Marco von Atzigen, Florian Wanivenhaus, Caroline Neuhaus, José Spirig, Davide Scaramuzza, Reto Sutter, Jess Snedeker, Mazda Farshad, Philipp Fürnstahl
In surgical navigation, finding correspondence between preoperative plan and intraoperative anatomy, the so-called registration task, is imperative.