Skip to main content
Top
Published in: International Journal of Computer Assisted Radiology and Surgery 5/2022

04-04-2022 | Original Article

Disparity-constrained stereo endoscopic image super-resolution

Authors: Tianyi Zhang, Yun Gu, Xiaolin Huang, Jie Yang, Guang-Zhong Yang

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 5/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Purpose

With the increasing usage of stereo cameras in computer-assisted surgery techniques, surgeons can benefit from better 3D context of the surgical site in minimally invasive operations. However, since stereo cameras are placed together at the confined endoscope tip, the size of lens and sensors is limited, resulting in low resolution of stereo endoscopic images. How to effectively exploit and utilize stereo information in stereo endoscopic super-resolution (SR) becomes a challenging problem.

Methods

In this work, we propose a disparity-constrained stereo super-resolution network (DCSSRnet) to reconstruct images using a stereo image pair. In particular, a disparity constraint mechanism is incorporated into the generation of SR images in the deep neural network framework with effective feature extractors and atrous parallax attention modules.

Results

Extensive experiments were conducted to evaluate the performance of proposed DCSSRnet on the da Vinci dataset and Medtronic dataset. The results on endoscopic image datasets demonstrate that the proposed approach produces a more effective improvement over current SR methods on both quantitative measurements. The ablation studies further verify the effectiveness of the components of the proposed framework.

Conclusion

The proposed DCSSRnet provides a promising solution on enhancing the spatial resolution of stereo endoscopic image pairs. Specifically, the disparity consistency of the stereo image pair provides informative supervision for image reconstruction. The proposed model can serve as a tool for improving the quality of stereo endoscopic images of endoscopic surgery systems.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
13.
go back to reference Chen Y, Shi F, Christodoulou A G, Xie Y, Zhou Z, Li D (2018) Efficient and accurate MRI super-resolution using a generative adversarial network and 3D multi-level densely connected network. In Proceedings of International conference on medical image computing and computer-assisted intervention (MICCAI): 91–99. https://doi.org/10.1007/978-3-030-00928-1_11 Chen Y, Shi F, Christodoulou A G, Xie Y, Zhou Z, Li D (2018) Efficient and accurate MRI super-resolution using a generative adversarial network and 3D multi-level densely connected network. In Proceedings of International conference on medical image computing and computer-assisted intervention (MICCAI): 91–99. https://​doi.​org/​10.​1007/​978-3-030-00928-1_​11
14.
go back to reference Zhao C, Carass A, Dewey B E, Woo J, Oh J, Calabresi P A, Reich D S, Sati P, Pham D L, Prince J L (2018). A deep learning based anti-aliasing self super-resolution algorithm for MRI. In Proceedings of International conference on medical image computing and computer-assisted intervention (MICCAI): 100–108. https://doi.org/10.1007/978-3-030-00928-1_12 Zhao C, Carass A, Dewey B E, Woo J, Oh J, Calabresi P A, Reich D S, Sati P, Pham D L, Prince J L (2018). A deep learning based anti-aliasing self super-resolution algorithm for MRI. In Proceedings of International conference on medical image computing and computer-assisted intervention (MICCAI): 100–108. https://​doi.​org/​10.​1007/​978-3-030-00928-1_​12
19.
go back to reference Wang R, Zhang D, Li Q, Zhou XY, Lo B (2021) Real-time Surgical Environment Enhancement for Robot-Assisted Minimally Invasive Surgery Based on Super-Resolution. In Proceedings of international conference on robotics and automation (ICRA): 3434–3440 Wang R, Zhang D, Li Q, Zhou XY, Lo B (2021) Real-time Surgical Environment Enhancement for Robot-Assisted Minimally Invasive Surgery Based on Super-Resolution. In Proceedings of international conference on robotics and automation (ICRA): 3434–3440
Metadata
Title
Disparity-constrained stereo endoscopic image super-resolution
Authors
Tianyi Zhang
Yun Gu
Xiaolin Huang
Jie Yang
Guang-Zhong Yang
Publication date
04-04-2022
Publisher
Springer International Publishing
Published in
International Journal of Computer Assisted Radiology and Surgery / Issue 5/2022
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-022-02611-5

Other articles of this Issue 5/2022

International Journal of Computer Assisted Radiology and Surgery 5/2022 Go to the issue

Premium Partner