Physical Intelligence Article 2018

Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots

Thumb ticker sm mehmet
Physical Intelligence
  • Postdoctoral Researcher
Thumb ticker sm metin eth vertical small
Physical Intelligence
Guest Researcher
Screenshot 2018 5 9 1803 01048 pdf

Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is demonstrated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors 1.58 to 2.17 cm.

Author(s): Mehmet Turan and Yasin Almalioglu and Evin Pinar Ornek and Helder Araujo and Mehmet Fatih Yanik and Metin Sitti
Journal: ArXiv e-prints
Year: 2018
Month: March
Day: 2
Bibtex Type: Article (article)
URL: https://arxiv.org/abs/1803.01048
Electronic Archiving: grant_archive
Eprint: 1803.01048

BibTex

@article{2018arXiv180301048T,
  title = {Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots},
  journal = {ArXiv e-prints},
  abstract = {Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is demonstrated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors 1.58 to 2.17 cm. },
  month = mar,
  year = {2018},
  slug = {2018arxiv180301048t},
  author = {Turan, Mehmet and Almalioglu, Yasin and Ornek, Evin Pinar and Araujo, Helder and Yanik, Mehmet Fatih and Sitti, Metin},
  eprint = {1803.01048},
  url = {https://arxiv.org/abs/1803.01048},
  month_numeric = {3}
}