JACIII Vol.20 No.3 pp. 448-454
doi: 10.20965/jaciii.2016.p0448


Underwater 3D Imaging Using a Fiber-Based Endoscopic System for Arthroscopic Surgery

Zhongjie Long*,** and Kouki Nagamune*,***

*Department of Human and Artificial Intelligent Systems, University of Fukui
Fukui 910-8507, Japan
**Beijing Information Science and Technology University
Beijing 100192, China
***Department of Orthopaedic Surgery, Kobe University
Kobe 650-0017, Japan

October 30, 2015
February 18, 2016
Online released:
May 19, 2016
May 19, 2016
endoscope, optical fiber, surface reconstruction, arthroscopy, minimally invasive surgery

Arthroscopic surgery is a minimally invasive surgical procedure that is widely used on joints. However, conventional endoscope-based arthroscopic surgery does not provide stereoscopic information to the surgeon. To overcome this limitation, we have developed a modified endoscopic system that uses an optical fiber (1 mm diameter) for three-dimensional imaging of knee joints. Our endoscopic system is able to operate underwater in real time. It consists of a laser beam that is projected on the surface of the object to be imaged via an optical fiber. A prism is used to decrease the length and diameter of baseline and endoscope tube, respectively. The small diameter (8 mm) of our endoscope makes it extremely convenient for application in arthroscopic surgery. The feasibility of the proposed system has been demonstrated via experiments on synthetic knee joints.

  1. [1] G. S. Litynski, “Endoscopic surgery: the history, the pioneers,”World J. of Surgery, Vol.23, No.8, pp. 745-753, 1999.
  2. [2] J. Wickham, “The new surgery,” British Medical J. (Clinical ResearchEd.), Vol.295, No.6613, pp. 1581-1582, 1987.
  3. [3] R. Satava, “3-D vision technology applied to advanced minimallyinvasive surgery systems,” Surgical Endoscopy, Vol.7, No.5, pp. 429-431, 1993.
  4. [4] K. Cleary and T. M. Peters, “Image-guided interventions: technologyreview and clinical applications,” Annual Review of Biomedical Engineering, Vol.12, pp. 119-142, 2010.
  5. [5] Z. Yaniv and K. Cleary, “Image-guided procedures: A review,”Computer Aided Interventions and Medical Robotics, Vol.3, 2006.
  6. [6] D. Stoyanov, “Stereoscopic scene flow for robotic assisted minimallyinvasive surgery,” Proc. of Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 479-486, 2012.
  7. [7] D. Stoyanov, A. Darzi, and G. Z. Yang, “Dense 3D depth recoveryfor soft tissue deformation during robotically assisted laparoscopicsurgery,” Proc. of Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 41-48, 2004.
  8. [8] D. J. Mirota, M. Ishii, and G. D. Hager, “Vision-based navigationin image-guided interventions,” Annual Review of Biomedical Engineering,Vol.13, pp. 297-319, 2011.
  9. [9] F. Mourgues, F. Devemay, and È. Coste-Manière, “3D reconstructionof the operating field for image overlay in 3D-endoscopicsurgery,” Proc. of IEEE and ACM Int. Symp. on Augmented Reality, pp. 191-192, 2001.
  10. [10] F. Devernay, F. Mourgues, and È. Coste-Manière, “Towards endoscopicaugmented reality for robotically assisted minimally invasivecardiac surgery,” Proc. of IEEE and ACM Int. Workshop on Augmented Reality, pp. 16-20, 2001.
  11. [11] C.-H. Wu, Y.-C. Chen, C.-Y. Liu, C.-C. Chang, and Y.-N. Sun,“Automatic extraction and visualization of human inner structuresfrom endoscopic image sequences,” Proc. of SPIE 5369, Medical Imaging, pp. 464-473, 2004.
  12. [12] D. Stoyanov, G. P. Mylonas, F. Deligianni, A. Darzi, and G. Z.Yang, “Soft-tissue motion tracking and structure estimation forrobotic assisted MIS procedures,” Proc. of Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 139-146, 2005.
  13. [13] H. Haneishi, T. Ogura, and Y. Miyake, “Profilometry of a gastrointestinalsurface by an endoscope with laser beam projection,” Optics Letters, Vol.19, No.9, pp. 601-603, 1994.
  14. [14] K. Hasegawa, K. Noda, and Y. Sato, “Electronic endoscope systemfor shape measurement,” Proc. of IEEE Int. Conf. on Pattern Recognition, pp. 761-764, 2002.
  15. [15] N. T. Clancy, D. Stoyanov, L. Maier-Hein, A. Groch, G.-Z. Yang,and D. S. Elson, “Spectrally encoded fiber-based structured lightingprobe for intraoperative 3D imaging,” Biomedical Optics Express,Vol.2, No.11, pp. 3119-3128, 2011.
  16. [16] Z. Long and K. Nagamune, “A Marching Cubes Algorithm: Applicationfor Three-dimensional Surface Reconstruction Based on Endoscopeand Optical Fiber,” Information, Vol.18, No.4, pp. 1425-1437, 2015.
  17. [17] Y. Matsusue, T. Yamamuro, and H. Hama, “Arthroscopic multipleosteochondral transplantation to the chondral defect in the knee associatedwith anterior cruciate ligament disruption,” Arthroscopy: The J. of Arthr. & Related Surgery, Vol.9, No.3, pp. 318-321, 1993.
  18. [18] M. Brittberg, A. Lindahl, A. Nilsson, C. Ohlsson, O. Isaksson,and L. Peterson, “Treatment of deep cartilage defects in the kneewith autologous chondrocyte transplantation,” New England J. of Medicine, Vol.331, No.14, pp. 889-895, 1994.
  19. [19] L. Hangody, G. Kish, Z. Kárpáti, and R. Eberhart, “Osteochondralplugs: Autogenousosteochondral mosaicplasty for the treatmentof focal chondral and osteochondral articular defects,” Operative Techniques in Orthopaedics, Vol.7, No.4, pp. 312-322, 1997.
  20. [20] L. Maier-Hein, P. Mountney, A. Bartoli, H. Elhawary, D. Elson,A. Groch, A. Kolb, M. Rodrigues, J. Sorger, S. Speidel, andD. Stoyanov, “Optical techniques for 3D surface reconstruction incomputer-assisted laparoscopic surgery,” Medical Image Analysis, Vol.17, No.8, pp. 974-996, 2013.
  21. [21] M. Hu, G. Penney, M. Figl, P. Edwards, F. Bello, R. Casula,D. Rueckert, and D. Hawkes, “Reconstruction of a 3D surface fromvideo that is robust to missing data and outliers: Application to minimallyinvasive surgery using stereo and mono endoscopes,” Medical Image Analysis, Vol.16, No.3, pp. 597-611, 2012.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Mar. 28, 2017