AR navigation system for neurosurgery

Yuichiro Akatsuka; Takakazu Kawamata; Masakazu Fujii; Yukihito Furuhashi; Akito Saito; Takao Shibasaki; Hiroshi Iseki; Tomokatsu Hori

doi:10.1007/978-3-540-40899-4_86

AR navigation system for neurosurgery

Yuichiro Akatsuka, Takakazu Kawamata, Masakazu Fujii, Yukihito Furuhashi, Akito Saito, Takao Shibasaki, Hiroshi Iseki, Tomokatsu Hori

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

This paper presents a navigation system for an endoscope which can be used for neurosurgery. In this system, a wire frame model of a target tumor and other significant anatomical landmarks are superimposed in real-time onto live video images taken from the endoscope. The wire frame model is generated from a CT/MRI slice images. Overlaid images are simultaneously displayed in the same monitor using the picture-in-picture function so that the surgeon can concentrate on the single monitor during the surgery. The system measures the position and orientation of the patient using specially designed non-contact sensing devices mounted on the endoscpe. Based on this real-time measurement, the system displays other useful information about the navigation as well as the rendered wire frame. The accuracy of registration between the wire frame model and the actual live view is less than 2mm. We applied this AR navigation clinically in surgical resection of pituitary tumors in six cases, and verified its performance and effectiveness.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2000 - 3rd International Conference, Proceedings
Editors	Scott L. Delp, Anthony M. DiGoia, Branislav Jaramaz
Publisher	Springer Verlag
Pages	833-838
Number of pages	6
ISBN (Print)	3540411895, 9783540411895
DOIs	https://doi.org/10.1007/978-3-540-40899-4_86
Publication status	Published - 2000
Externally published	Yes
Event	3rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2000 - Pittsburgh, United States Duration: 2000 Oct 11 → 2000 Oct 14

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1935
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	3rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2000
Country/Territory	United States
City	Pittsburgh
Period	00/10/11 → 00/10/14

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-40899-4_86

Cite this

Akatsuka, Y., Kawamata, T., Fujii, M., Furuhashi, Y., Saito, A., Shibasaki, T., Iseki, H., & Hori, T. (2000). AR navigation system for neurosurgery. In S. L. Delp, A. M. DiGoia, & B. Jaramaz (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2000 - 3rd International Conference, Proceedings (pp. 833-838). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1935). Springer Verlag. https://doi.org/10.1007/978-3-540-40899-4_86

AR navigation system for neurosurgery. / Akatsuka, Yuichiro; Kawamata, Takakazu; Fujii, Masakazu et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2000 - 3rd International Conference, Proceedings. ed. / Scott L. Delp; Anthony M. DiGoia; Branislav Jaramaz. Springer Verlag, 2000. p. 833-838 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1935).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Akatsuka, Y, Kawamata, T, Fujii, M, Furuhashi, Y, Saito, A, Shibasaki, T, Iseki, H & Hori, T 2000, AR navigation system for neurosurgery. in SL Delp, AM DiGoia & B Jaramaz (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2000 - 3rd International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1935, Springer Verlag, pp. 833-838, 3rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2000, Pittsburgh, United States, 00/10/11. https://doi.org/10.1007/978-3-540-40899-4_86

Akatsuka Y, Kawamata T, Fujii M, Furuhashi Y, Saito A, Shibasaki T et al. AR navigation system for neurosurgery. In Delp SL, DiGoia AM, Jaramaz B, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2000 - 3rd International Conference, Proceedings. Springer Verlag. 2000. p. 833-838. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-40899-4_86

Akatsuka, Yuichiro ; Kawamata, Takakazu ; Fujii, Masakazu et al. / AR navigation system for neurosurgery. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2000 - 3rd International Conference, Proceedings. editor / Scott L. Delp ; Anthony M. DiGoia ; Branislav Jaramaz. Springer Verlag, 2000. pp. 833-838 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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N2 - This paper presents a navigation system for an endoscope which can be used for neurosurgery. In this system, a wire frame model of a target tumor and other significant anatomical landmarks are superimposed in real-time onto live video images taken from the endoscope. The wire frame model is generated from a CT/MRI slice images. Overlaid images are simultaneously displayed in the same monitor using the picture-in-picture function so that the surgeon can concentrate on the single monitor during the surgery. The system measures the position and orientation of the patient using specially designed non-contact sensing devices mounted on the endoscpe. Based on this real-time measurement, the system displays other useful information about the navigation as well as the rendered wire frame. The accuracy of registration between the wire frame model and the actual live view is less than 2mm. We applied this AR navigation clinically in surgical resection of pituitary tumors in six cases, and verified its performance and effectiveness.

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AR navigation system for neurosurgery

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