Search Results for author: Mazda Farshad

Found 9 papers, 0 papers with code

Creating a Digital Twin of Spinal Surgery: A Proof of Concept

no code implementations25 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.

3D Reconstruction Anatomy

Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement

no code implementations9 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.

Anatomy

Next-generation Surgical Navigation: Marker-less Multi-view 6DoF Pose Estimation of Surgical Instruments

no code implementations5 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.

Anatomy Pose Estimation

Improved Techniques for the Conditional Generative Augmentation of Clinical Audio Data

no code implementations5 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.

Data Augmentation

Conditional Generative Data Augmentation for Clinical Audio Datasets

no code implementations22 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.

Data Augmentation Generative Adversarial Network

Registration made easy -- standalone orthopedic navigation with HoloLens

no code implementations17 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.

Anatomy

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