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Real-time marker-free patient registration for electromagnetic navigated bronchoscopy: a phantom study

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

To perform bronchoscopy safely and smoothly, it is very important to develop a bronchoscopic guidance system. Transbronchial lung biopsy (TBLB) with a bronchoscopic guidance system especially should permit safe image-guided procedures. Recently, electromagnetic tracking (EMT) is utilized to track the tip of the bronchoscope camera in real time. For most tracking methods using position sensors, registration between tracking data and previously acquired reference image data, such as CT image, is performed using natural landmarks of the patient or fiducial markers attached to the patient, whose positions need to be measured manually by the physician before the actual bronchoscopy. Therefore, this paper proposes a marker-free CT-to-patient registration method utilizing bronchoscope’s position and orientation obtained by the EMT.

Methods

We developed a guidance system that is able to track the tip of the bronchoscope camera in real time. In the case of a guidance system that uses position sensors, natural landmarks of the patient or fiducial markers attached to the patient are needed to obtain the correspondence between EMT outputs and previously acquired reference image data, such as CT image. This paper proposes a registration method without landmarks or fiducials by estimating the transformation matrix between the patient and the CT image taken prior to the bronchoscopic examination. This estimation is performed by computing correspondences between the outputs of the EMT sensor and airways extracted from the CT image. As ambiguities between EMT measurements and their corresponding airway branches may arise at airway bifurcations, we introduce a stable airway branch selection mechanism for improving the robustness of the estimation of the transformation matrix. To evaluate the performance of the proposed method, we applied the method to a rubber bronchial phantom and added virtual breathing motion to the sensor output.

Results

Experimental results show that the accuracy of our proposed method is within 2.0−3.0 mm (without breathing motion) and 2.5−3.5 mm (with breathing motion). The proposed method could also track a bronchoscope camera in real time.

Conclusions

We developed a method for CT-to-patient registration using a position sensor without fiducial markers and natural landmarks. Endoscopic guided biopsy of lung lesions is feasible using a marker-free CT-to-patient registration method.

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References

  1. Vining DJ, Shitrin RY, Haponik EF, Liu K, Choplin RH (1994) Virtual bronchoscopy. Radiology, vol 193(P), Supplement to radiology (RSNA Scientific Program), p 261

  2. Geiger B, Kikinis R (1995) Simulation of endoscopy, Computer vision, virtual reality and robotics in medicine, LNCS 905. Springer, pp 277–281

  3. Rubin G, Beaulieu C, Argiro V, Ringl H, Norbash A, Feller J, Dake M, Jeffrey R, Napel S (1996) Perspective volume rendering of CT and MR images: applications for endoscopic imaging. Radiology 199: 321–330

    PubMed  CAS  Google Scholar 

  4. Mori K, Urano A, Hasegawa J, Toriwaki J, Anno H, Katada K (1996) Virtualized endoscope system—an application of virtual reality technology to diagnostic aid. IEICE Trans Inf Syst E79–D(6): 809–819

    Google Scholar 

  5. Hong L, Muraki S, Kaufman A, Bartz D, He T (1997) Virtual voyage: interactive navigation in the human colon. In: Proceedings of the 24th annual conference on computer graphics and interactive techniques (SIGGRAPH’97), pp 27–34

  6. Rogalla, P, Terwisschavan Scheltinga, J, Hamm, B (eds) (2001) Virtual endoscopy and related 3D techniques. Springer, Berlin

    Google Scholar 

  7. Caramella, D, Bartolozzi, C (eds) (2002) 3D image processing—techniques and clinical application. Springer, Berlin

    Google Scholar 

  8. Bricault I, Ferretti G, Cinquin P (1998) Registration of real and CT-derived virtual bronchoscopic images to assist transbronchial biopsy. IEEE Trans Med Imaging 17(5): 703–714

    Article  PubMed  CAS  Google Scholar 

  9. Helferty JP, Higgins WE (2001) Technique for registering 3D virtual CT images to endoscopic video. In: Proceedings of international conference on image processing (ICIP2001), pp 893–896

  10. Merritt SA, Rai L, Higgins WE (2006) Real-time CT-video registration for continuous endoscopic guidance. In: Proceedings of SPIE medical imaging, vol 6143, pp 614313-1–614313-15

  11. Mori K, Deguchi D, Sugiyama J, Suenaga Y, Toriwaki J, Maurer CR Jr, Takabatake H, Natori H (2002) Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images. Med Image Anal 6: 321–336

    Article  PubMed  CAS  Google Scholar 

  12. Schneider A, Hautmann H, Barfuss H, Pinkau T, Peltz F, Feussner H, Wichert A (2004) Real-time image tracking of a flexible bronchoscope. In: Proceedings of CARS2004, vol 1268, pp 753–757

  13. Deligianni F, Chung AJ, Yang GZ (2006) Nonrigid 2-D/3-D registration for patient specific bronchoscopy simulation with statistical shape modeling: phantom validation. IEEE Trans Med Imaging 25(11): 1462–1471

    Article  PubMed  Google Scholar 

  14. Wegner I, Biederer J, Tetzlaff R, Wolf I, Meinzer H (2007) Evaluation and extension of a navigation system for bronchoscopy inside human lungs. In: Proceedings of SPIE medical imaging 2007, vol 6509, pp 65091H-1–65091H-12

  15. Klein T, Traub J, Hautmann H, Ahmadian A, Navab N (2007) Fiducial-free registration procedure for navigated bronchoscopy. In: Proceedings of the 10th international conference on medical image computing and computer assisted intervention (MICCAI2007), Part I, LNCS, vol 4791, pp 475–482

  16. Deguchi D, Ishitani K, Kitasaka T, Mori K, Suenaga Y, Takabatake H, Mori M, Natori H (2007) A method for bronchoscope tracking using position sensor without fiducial markers. In: Proceedings of SPIE medical imaging 2007, vol 6511, pp 65110N-1–65110N-12

  17. Mori K, Deguchi D, Ishitani K, Kitasaka T, Suenaga Y, Hasegawa Y, Imaizumi K, Takabatake H (2007) Bronchoscope tracking without fiducial markers using ultra-tiny electromagnetic tracking system and its evaluation in different environments. In: Proceedings of the 10th international conference on medical image computing and computer assisted intervention (MICCAI2007), Part II, LNCS vol 4792, pp 644–651

  18. Mori K, Deguchi D, Kitasaka T, Suenaga Y, Hasegawa Y, Imaizumi K, Takabatake H (2008) Improvement of accuracy of marker-free bronchoscope tracking using electromagnetic tracker based on bronchial branch information. In: Proceedings of the 11th international conference on medical image computing and computer assisted intervention (MICCAI2008), Part II, LNCS, vol 5242, pp 535–542

  19. Besl PJ, McKay HD (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal Mach Intell 14(2): 239–256

    Article  Google Scholar 

  20. Tsai RY, Lenz RK (1988) Real time versatile robotics hand/eye calibration using 3D machine vision. In: Proceedings of 1988 IEEE international conference on robotics and automation, pp 554–561

  21. Shahidi R, Bax MR, Maurer CR Jr, Johnson JA, Wilkinson EP, Wang B, West JB, Citardi MJ, Manwaring KH, Khadem R (2002) Implementation, calibration and accuracy testing of an image-enhanced endoscopy system. IEEE Trans Med Imaging 21(12): 1524–1535

    Article  PubMed  Google Scholar 

  22. Kitasaka T, Mori K, Hasegawa J, Toriwaki J (2002) A method for extraction of bronchus regions from 3D chest X-ray CT images by analyzing structural features of the bronchus. FORMA 17(4): 321–338

    Google Scholar 

  23. Feuerstein M, Kitasaka T, Mori K (2009) Adaptive branch tracing and image sharpening for airway tree extraction in 3-D chest CT. In: Proceedings of second international workshop on pulmonary image analysis, pp 273–284

  24. Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1999) Numerical recipes in C, the art of scientific computing second edition. Cambridge University Press, Cambridge, pp 321–336

    Google Scholar 

  25. Soper TD, Haynora DR, Glenny RW, Seibela EJ (2007) A model of respiratory airway motion for real-time tracking of an ultrathin bronchoscope. In: Proceedings of SPIE medical imaging 2007, vol 6511, pp 65110M-1–65110M-12

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Correspondence to Daisuke Deguchi.

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Deguchi, D., Feuerstein, M., Kitasaka, T. et al. Real-time marker-free patient registration for electromagnetic navigated bronchoscopy: a phantom study. Int J CARS 7, 359–369 (2012). https://doi.org/10.1007/s11548-011-0626-9

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  • DOI: https://doi.org/10.1007/s11548-011-0626-9

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