A real-time navigation system for laparoscopic surgery based on three-dimensional ultrasound using magneto-optic hybrid tracking configuration

Kozo Konishi, Masahiko Nakamoto, Yoshihiro Kakeji, Kazuo Tanoue, Hirofumi Kawanaka, Shohei Yamaguchi, Satoshi Ieiri, Yoshinobu Sato, Yoshihiko Maehara, Shinichi Tamura, Makoto Hashizume

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)

Abstract

Objectives: In laparoscopic liver surgery, intraoperative navigation is strongly recommended. We developed a navigation system based on intraoperative ultrasound (IOUS). The purpose of this study was to evaluate the usefulness and accuracy of this system using an animate model. Materials and methods: Augmented reality (AR) visualization superimposing three-dimensional ultrasound (3D-US) images onto captured laparoscopic live images was constructed. We employed magneto-optic hybrid tracking configuration and a rapid method of magnetic distortion correction. Twelve pigs and liver tumor mimics were used, and effects of magnetic distortion correction and accuracy of 3D-US navigation were evaluated. Results: Using magnetic distortion correction, tracking error was significantly reduced. Each ultrasound scanning time was within 30 s, and the time to generate 3D-US images was within 3 min. All tumor mimics were successfully puncture-guided with navigation. Registration accuracy was significantly improved from 17.2± 5.27 to 1.96 ±0.87 mm. Conclusion: We developed an AR navigation system based on IOUS. Experimental results showed that the proposed method was effective, and could be used in clinical settings. 3D-US, as an imaging modality allows real-time imaging regardless of organ shifts or distortion.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalInternational Journal of Computer Assisted Radiology and Surgery
Volume2
Issue number1
DOIs
Publication statusPublished - 2007

All Science Journal Classification (ASJC) codes

  • Surgery
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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