Abstract

Three dimensional quantification of organ shape and structure during minimally invasive surgery (MIS) could enhance precision by allowing the registration of multi-modal or pre-operative image data (US/MRI/CT) with the live optical image. Structured illumination is one technique to obtain 3D information through the projection of a known pattern onto the tissue, although currently these systems tend to be used only for macroscopic imaging or open procedures rather than in endoscopy. To account for occlusions, where a projected feature may be hidden from view and/or confused with a neighboring point, a flexible multispectral structured illumination probe has been developed that labels each projected point with a specific wavelength using a supercontinuum laser. When imaged by a standard endoscope camera they can then be segmented using their RGB values, and their 3D coordinates calculated after camera calibration. The probe itself is sufficiently small (1.7 mm diameter) to allow it to be used in the biopsy channel of commonly used medical endoscopes. Surgical robots could therefore also employ this technology to solve navigation and visualization problems in MIS, and help to develop advanced surgical procedures such as natural orifice translumenal endoscopic surgery.

© 2011 OSA

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References

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2011 (1)

J. Geng, “DLP-based structured light 3D imaging technologies and applications,” Proc. SPIE7923, 79320B, 79320B-15 (2011).
[CrossRef]

2008 (2)

2007 (1)

S. Voros, J.-A. Long, and P. Cinquin, “Automatic detection of instruments in laparoscopic images: a first step towards high-level command of robotic endoscopic holders,” Int. J. Robot. Res.26(11-12), 1173–1190 (2007).
[CrossRef]

2006 (2)

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

2005 (1)

D. Stoyanov, A. Darzi, and G.-Z. Yang, “A practical approach towards accurate dense 3D depth recovery for robotic laparoscopic surgery,” Comput. Aided Surg.10(4), 199–208 (2005).
[PubMed]

2004 (2)

J. J. Schwartz and G. R. Lichtenstein, “Magnification endoscopy, chromoendoscopy and other novel techniques in evaluation of patients with IBD,” Tech. Gastrointest. Endosc.6(4), 182–188 (2004).
[CrossRef]

J. Salvi, J. Pagès, and J. Batlle, “Pattern codification strategies in structured light systems,” Pattern Recognit.37(4), 827–849 (2004).
[CrossRef]

2003 (1)

1999 (1)

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

1998 (1)

J. Batlle, E. Mouaddib, and J. Salvi, “Recent progress in coded structured light as a technique to solve the correspondence problem: a survey,” Pattern Recognit.31(7), 963–982 (1998).
[CrossRef]

1932 (1)

T. Smith and J. Guild, “The C.I.E. colorimetric standards and their use,” Trans. Opt. Soc.33(3), 73–134 (1932).
[CrossRef]

Barratt, D. C.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

Batlle, J.

J. Salvi, J. Pagès, and J. Batlle, “Pattern codification strategies in structured light systems,” Pattern Recognit.37(4), 827–849 (2004).
[CrossRef]

J. Batlle, E. Mouaddib, and J. Salvi, “Recent progress in coded structured light as a technique to solve the correspondence problem: a survey,” Pattern Recognit.31(7), 963–982 (1998).
[CrossRef]

Carter, T. J.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

Chan, C. S. K.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

Chan, M.

Chandra, S.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Chen, H. J.

Cheung, T.-H.

Cinquin, P.

S. Voros, J.-A. Long, and P. Cinquin, “Automatic detection of instruments in laparoscopic images: a first step towards high-level command of robotic endoscopic holders,” Int. J. Robot. Res.26(11-12), 1173–1190 (2007).
[CrossRef]

Cox, T. C.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Darzi, A.

D. Stoyanov, A. Darzi, and G.-Z. Yang, “A practical approach towards accurate dense 3D depth recovery for robotic laparoscopic surgery,” Comput. Aided Surg.10(4), 199–208 (2005).
[PubMed]

de Cunha, D. A.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Edwards, P. J.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Fang, J.

Fenlon, M. R.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Fleig, O.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Fu, K. I.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Fujii, T.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Fujimori, T.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Gaston, R. P.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Geng, J.

J. Geng, “DLP-based structured light 3D imaging technologies and applications,” Proc. SPIE7923, 79320B, 79320B-15 (2011).
[CrossRef]

Gleeson, M. J.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Guild, J.

T. Smith and J. Guild, “The C.I.E. colorimetric standards and their use,” Trans. Opt. Soc.33(3), 73–134 (1932).
[CrossRef]

Hawkes, D. J.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Hill, D. L.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Kato, S.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

King, A. P.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Koba, I.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Lichtenstein, G. R.

J. J. Schwartz and G. R. Lichtenstein, “Magnification endoscopy, chromoendoscopy and other novel techniques in evaluation of patients with IBD,” Tech. Gastrointest. Endosc.6(4), 182–188 (2004).
[CrossRef]

Lin, W.

Long, J.-A.

S. Voros, J.-A. Long, and P. Cinquin, “Automatic detection of instruments in laparoscopic images: a first step towards high-level command of robotic endoscopic holders,” Int. J. Robot. Res.26(11-12), 1173–1190 (2007).
[CrossRef]

Mannss, J.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Matsuda, T.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Maurer, C. R. J.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Mouaddib, E.

J. Batlle, E. Mouaddib, and J. Salvi, “Recent progress in coded structured light as a technique to solve the correspondence problem: a survey,” Pattern Recognit.31(7), 963–982 (1998).
[CrossRef]

Pagès, J.

J. Salvi, J. Pagès, and J. Batlle, “Pattern codification strategies in structured light systems,” Pattern Recognit.37(4), 827–849 (2004).
[CrossRef]

Penney, G. P.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

Qu, J. Y.

Saito, Y.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Salvi, J.

J. Salvi, J. Pagès, and J. Batlle, “Pattern codification strategies in structured light systems,” Pattern Recognit.37(4), 827–849 (2004).
[CrossRef]

J. Batlle, E. Mouaddib, and J. Salvi, “Recent progress in coded structured light as a technique to solve the correspondence problem: a survey,” Pattern Recognit.31(7), 963–982 (1998).
[CrossRef]

Sano, Y.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Schwartz, J. J.

J. J. Schwartz and G. R. Lichtenstein, “Magnification endoscopy, chromoendoscopy and other novel techniques in evaluation of patients with IBD,” Tech. Gastrointest. Endosc.6(4), 182–188 (2004).
[CrossRef]

Slomczykowski, M.

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

Smith, T.

T. Smith and J. Guild, “The C.I.E. colorimetric standards and their use,” Trans. Opt. Soc.33(3), 73–134 (1932).
[CrossRef]

Stoyanov, D.

D. Stoyanov, A. Darzi, and G.-Z. Yang, “A practical approach towards accurate dense 3D depth recovery for robotic laparoscopic surgery,” Comput. Aided Surg.10(4), 199–208 (2005).
[PubMed]

Strong, A. J.

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Voros, S.

S. Voros, J.-A. Long, and P. Cinquin, “Automatic detection of instruments in laparoscopic images: a first step towards high-level command of robotic endoscopic holders,” Int. J. Robot. Res.26(11-12), 1173–1190 (2007).
[CrossRef]

Wu, T. T.

Yang, G.-Z.

D. Stoyanov, A. Darzi, and G.-Z. Yang, “A practical approach towards accurate dense 3D depth recovery for robotic laparoscopic surgery,” Comput. Aided Surg.10(4), 199–208 (2005).
[PubMed]

Yim, S.-F.

Yoshida, S.

S. Kato, K. I. Fu, Y. Sano, T. Fujii, Y. Saito, T. Matsuda, I. Koba, S. Yoshida, and T. Fujimori, “Magnifying colonoscopy as a non-biopsy technique for differential diagnosis of non-neoplastic and neoplastic lesions,” World J. Gastroenterol.12(9), 1416–1420 (2006).
[PubMed]

Zhang, J.

Zhou, C.

Appl. Opt. (1)

Comput. Aided Surg. (1)

D. Stoyanov, A. Darzi, and G.-Z. Yang, “A practical approach towards accurate dense 3D depth recovery for robotic laparoscopic surgery,” Comput. Aided Surg.10(4), 199–208 (2005).
[PubMed]

Int. J. Robot. Res. (1)

S. Voros, J.-A. Long, and P. Cinquin, “Automatic detection of instruments in laparoscopic images: a first step towards high-level command of robotic endoscopic holders,” Int. J. Robot. Res.26(11-12), 1173–1190 (2007).
[CrossRef]

Med. Image Anal. (1)

G. P. Penney, D. C. Barratt, C. S. K. Chan, M. Slomczykowski, T. J. Carter, P. J. Edwards, and D. J. Hawkes, “Cadaver validation of intensity-based ultrasound to CT registration,” Med. Image Anal.10(3), 385–395 (2006).
[CrossRef] [PubMed]

Opt. Express (1)

Opt. Lett. (1)

Pattern Recognit. (2)

J. Batlle, E. Mouaddib, and J. Salvi, “Recent progress in coded structured light as a technique to solve the correspondence problem: a survey,” Pattern Recognit.31(7), 963–982 (1998).
[CrossRef]

J. Salvi, J. Pagès, and J. Batlle, “Pattern codification strategies in structured light systems,” Pattern Recognit.37(4), 827–849 (2004).
[CrossRef]

Proc. SPIE (1)

J. Geng, “DLP-based structured light 3D imaging technologies and applications,” Proc. SPIE7923, 79320B, 79320B-15 (2011).
[CrossRef]

Stud. Health Technol. Inform. (1)

P. J. Edwards, A. P. King, D. J. Hawkes, O. Fleig, C. R. J. Maurer, D. L. Hill, M. R. Fenlon, D. A. de Cunha, R. P. Gaston, S. Chandra, J. Mannss, A. J. Strong, M. J. Gleeson, and T. C. Cox, “Stereo augmented reality in the surgical microscope,” Stud. Health Technol. Inform.62, 102–108 (1999).
[PubMed]

Tech. Gastrointest. Endosc. (1)

J. J. Schwartz and G. R. Lichtenstein, “Magnification endoscopy, chromoendoscopy and other novel techniques in evaluation of patients with IBD,” Tech. Gastrointest. Endosc.6(4), 182–188 (2004).
[CrossRef]

Trans. Opt. Soc. (1)

T. Smith and J. Guild, “The C.I.E. colorimetric standards and their use,” Trans. Opt. Soc.33(3), 73–134 (1932).
[CrossRef]

World J. Gastroenterol. (1)

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Figures (6)

Fig. 1
Fig. 1

(a) Broadband laser light from the supercontinuum is dispersed by an SF-11 prism, which is then coupled into the fibers (50 μm core) at the array end of the probe. The projected pattern is a magnified image of the end face of the bundle formed by the projection lens. (b) Emission spectrum of the supercontinuum laser source, with the wavelength range used by the probe indicated between the dashed lines.

Fig. 2
Fig. 2

Spot segmentation and 3D calibration. (a) Cartoon image showing three projected spots, having different RGB values. (b) Each RGB triplet is converted to xy coordinates. A line projected through these coordinates from a reference white spot intersects the spectrum locus (dashed) at the dominant wavelength of the pixel. (c) RGB pixels are replaced by the calculated wavelength to form a greyscale ‘λ-space’ image which can be thresholded to find the centroids of spots of a particular wavelength. (d) Epipolar geometry showing different positions of a calibration object (c1-c3) and triangulation of points using spot centroids.

Fig. 3
Fig. 3

(a) RGB image of pattern recorded by camera. (b) λ-space image with centroids of spots. (c) Plot showing spot wavelength as calculated by the segmentation algorithm against the wavelength measured using a spectrometer. The transmission response of the camera’s filters (normalized to 1) is overlaid and the identity line is shown in black. The error bars indicate ± 1 standard deviation.

Fig. 4
Fig. 4

Calculated wavelength of a set of spots projected onto surfaces of different colors. (a) Blue and red card. (b) Ex vivo tissue: porcine intestine (inset, top left) and lamb kidney (inset, bottom right). The error bars represent ± 1 standard deviation.

Fig. 5
Fig. 5

Three dimensional calibration and validation. (a) Origin and propagation direction of projected spots with respect to the camera (origin) as determined during calibration routine. (b) Planar object. (c) Cylindrical object, diameter = 81 mm. (d) Cross-section of cylindrical object with least-squares fit.

Fig. 6
Fig. 6

Three-dimensional reconstruction of ex vivo tissue. (a) Porcine liver, ‘step’. (b) Ovine kidney, convex curve. (c) Porcine liver, convex curve. (d) Porcine tissue, border between fatty tissue and liver. (e) Porcine liver, ‘valley’.

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