no code implementations • 19 Feb 2024 • Jan Emily Mangulabnan, Roger D. Soberanis-Mukul, Timo Teufel, Manish Sahu, Jose L. Porras, S. Swaroop Vedula, Masaru Ishii, Gregory Hager, Russell H. Taylor, Mathias Unberath
Purpose: Preoperative imaging plays a pivotal role in sinus surgery where CTs offer patient-specific insights of complex anatomy, enabling real-time intraoperative navigation to complement endoscopy imaging.
no code implementations • 22 Oct 2023 • Jan Emily Mangulabnan, Roger D. Soberanis-Mukul, Timo Teufel, Isabela Hernández, Jonas Winter, Manish Sahu, Jose L. Porras, S. Swaroop Vedula, Masaru Ishii, Gregory Hager, Russell H. Taylor, Mathias Unberath
In this work, we perform a quantitative analysis of a self-supervised approach for sinus reconstruction using endoscopic sequences paired with optical tracking and high-resolution computed tomography acquired from nine ex-vivo specimens.
no code implementations • 5 Apr 2023 • Yuxin Chen, Anna Goodridge, Manish Sahu, Aditi Kishore, Seena Vafaee, Harsha Mohan, Katherina Sapozhnikov, Francis Creighton, Russell Taylor, Deepa Galaiya
Results: The force measurements on the tip of the surgical drill are validated with raw-egg drilling experiments, where a force sensor mounted below the egg serves as ground truth.
1 code implementation • 29 Dec 2022 • Zhaoshuo Li, Hongchao Shu, Ruixing Liang, Anna Goodridge, Manish Sahu, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
TAToo jointly tracks the rigid 3D motion of patient skull and surgical drill from stereo microscopic videos.
1 code implementation • 21 Nov 2022 • Hongchao Shu, Ruixing Liang, Zhaoshuo Li, Anna Goodridge, Xiangyu Zhang, Hao Ding, Nimesh Nagururu, Manish Sahu, Francis X. Creighton, Russell H. Taylor, Adnan Munawar, Mathias Unberath
Twin-S tracks and updates the virtual model in real-time given measurements from modern tracking technologies.
no code implementations • 2 Mar 2021 • Manish Sahu, Anirban Mukhopadhyay, Stefan Zachow
Conclusion: We show that our proposed approach can successfully exploit the unlabeled real endoscopic video frames and improve generalization performance over pure simulation-based training and the previous state-of-the-art.
no code implementations • 22 Jul 2020 • Manish Sahu, Ronja Strömsdörfer, Anirban Mukhopadhyay, Stefan Zachow
Surgical tool segmentation in endoscopic videos is an important component of computer assisted interventions systems.
2 code implementations • 24 Jan 2020 • Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat, Maximilian Löffler, Hans Liebl, Hongwei Li, Giles Tetteh, Jan Kukačka, Christian Payer, Darko Štern, Martin Urschler, Maodong Chen, Dalong Cheng, Nikolas Lessmann, Yujin Hu, Tianfu Wang, Dong Yang, Daguang Xu, Felix Ambellan, Tamaz Amiranashvili, Moritz Ehlke, Hans Lamecker, Sebastian Lehnert, Marilia Lirio, Nicolás Pérez de Olaguer, Heiko Ramm, Manish Sahu, Alexander Tack, Stefan Zachow, Tao Jiang, Xinjun Ma, Christoph Angerman, Xin Wang, Kevin Brown, Alexandre Kirszenberg, Élodie Puybareau, Di Chen, Yiwei Bai, Brandon H. Rapazzo, Timyoas Yeah, Amber Zhang, Shangliang Xu, Feng Hou, Zhiqiang He, Chan Zeng, Zheng Xiangshang, Xu Liming, Tucker J. Netherton, Raymond P. Mumme, Laurence E. Court, Zixun Huang, Chenhang He, Li-Wen Wang, Sai Ho Ling, Lê Duy Huynh, Nicolas Boutry, Roman Jakubicek, Jiri Chmelik, Supriti Mulay, Mohanasankar Sivaprakasam, Johannes C. Paetzold, Suprosanna Shit, Ivan Ezhov, Benedikt Wiestler, Ben Glocker, Alexander Valentinitsch, Markus Rempfler, Björn H. Menze, Jan S. Kirschke
Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel-level by a human-machine hybrid algorithm (https://osf. io/nqjyw/, https://osf. io/t98fz/).
no code implementations • 27 Oct 2016 • Manish Sahu, Anirban Mukhopadhyay, Angelika Szengel, Stefan Zachow
A transfer learning method for generating features suitable for surgical tools and phase recognition from the ImageNet classification features [1] is proposed here.