Abstract

The first and perhaps most important phase of a surgical procedure is the insertion of an intravenous (IV) catheter. Currently, this is performed manually by trained personnel. In some visions of future operating rooms, however, this process is to be replaced by an automated system. Experiments to determine the best NIR wavelengths to optimize vein contrast for physiological differences such as skin tone and/or the presence of hair on the arm or wrist surface are presented. For illumination our system is composed of a mercury arc lamp coupled to a 10nm band-pass spectrometer. A structured lighting system is also coupled to our multispectral system in order to provide 3D information of the patient arm orientation. Images of each patient arm are captured under every possible combinations of illuminants and the optimal combination of wavelengths for a given subject to maximize vein contrast using linear discriminant analysis is determined.

© 2009 Optical Society of America

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References

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  1. E. M. C. Hillman, "Experimental and theoretical investigations of near infrared tomographic imaging methods and clinical applications," Ph.D. thesis, Department of Medical Physics and Bioengineering - University College London (2002).
  2. E. M. C. Hillman and A. Moore, "All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast," Nat. Photonics 1(9), 526-530 (2007).
    [CrossRef]
  3. H. D. Zeman, G. Lovhoiden, C. Vrancken, and R. K. Danish, "Prototype vein contrast enhancer," Opt. Eng. 44, 086,401 (2005).
  4. V. C. Paquit, F. Meriaudeau, J. R. Price, and K. W. Tobin, "Simulation of skin reflectance images using 3D tissue modeling and multispectral Monte Carlo light propagation," in 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008. EMBS 2008, pp. 447-450 (2008).
  5. V. C. Paquit, J. R. Price, R. Seulin, F. Meriaudeau, R. H. Farahi, J. Kenneth W. Tobin, and T. L. Ferrell, "Nearinfrared imaging and structured light ranging for automatic catheter insertion," Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display 6141(1), 61411T (pages 9) (2006).
  6. V. C. Paquit, J. R. Price, F. Meriaudeau, J. Kenneth W. Tobin, and T. L. Ferrell, "Combining near-infrared illuminants to optimize venous imaging," Medical Imaging 2007: Visualization and Image-Guided Procedures 6509(1), 65090H (pages 9) (2007).
  7. R. Anderson and J. Parrish, "The Optics of Human Skin," Journal of Investigative Dermatology (1981).
    [CrossRef] [PubMed]
  8. Z. Zhang, "Flexible Camera Calibration by Viewing a Plane from Unknown Orientations," IEEE International Conference on Computer Vision 1, 666 (1999).
    [CrossRef]
  9. Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).
  10. R. A. Jarvis, "A Perspective on Range Finding Techniques for Computer Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence 5(2), 122-139 (1983).
    [CrossRef]
  11. J. Forest, J. M. Teixidor, J. Salvi, and E. Cabruja, "A Proposal for Laser Scanners Sub-pixel Accuracy Peak Detector," in Workshop on European Scientific and Industrial Collaboration, pp. 525-532 (Mickolj (Hungria), 2003).
  12. P. E. Bezier, Emploi des machines a commande numerique (Masson et Cie., 1970). Translated by A. R. Forrest and A. F. Pankhurst as Numerical Control - Mathematics and Applications, (John Wiley and Sons, Ltd., London, 1972).
  13. A. Efremov, V. Havran, and H.-P. Seidel, "Robust and numerically stable B’ezier clipping method for ray tracing NURBS surfaces," in SCCG ’05: Proceedings of the 21st spring conference on Computer graphics, pp. 127-135 (ACM, New York, NY, USA, 2005).
    [CrossRef]
  14. V. C. Paquit, F. Meriaudeau, J. R. Price, and K. W. Tobin, "Multispectral Imaging For Subcutaneous Structures Classification And Analysis," in International Topical Meeting on Optical Sensing and Artificial Vision, OSAV’2008, Saint Petersburg, Russia (2008).
    [PubMed]
  15. H. J. Noordmans, R. de Roode, and R. Verdaasdonk, "Compact multi-spectral imaging system for dermatology and neurosurgery," Proc. SPIE 6510, 65100I (2007).
  16. K. Fukunaga, Statistical Pattern Recognition (Morgan Kaufmann, 1990).
  17. C. Steger, "Extraction of curved lines from images," in Proceedings of the 13th International Conference on Pattern Recognition, Vol. 2, pp. 251-255 (1996).
  18. J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
    [CrossRef]
  19. J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
    [CrossRef]
  20. V. C. Paquit, "Imagerie multispectrale et mod’elisation 3D pour l’estimation quantitative des vaisseaux sanguins sous cutan’es," Ph.D. thesis, Universit’e de Bourgogne, Le Creusot, France (2008).

2007 (1)

E. M. C. Hillman and A. Moore, "All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast," Nat. Photonics 1(9), 526-530 (2007).
[CrossRef]

2006 (1)

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

2004 (1)

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

2003 (1)

Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).

1983 (1)

R. A. Jarvis, "A Perspective on Range Finding Techniques for Computer Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence 5(2), 122-139 (1983).
[CrossRef]

Abramoff, M.

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

Cesar, R.

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

Cree, M.

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

Healey, G.

Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).

Hillman, E. M. C.

E. M. C. Hillman and A. Moore, "All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast," Nat. Photonics 1(9), 526-530 (2007).
[CrossRef]

Jarvis, R. A.

R. A. Jarvis, "A Perspective on Range Finding Techniques for Computer Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence 5(2), 122-139 (1983).
[CrossRef]

Jelinek, H.

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

Leandro, J.

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

Moore, A.

E. M. C. Hillman and A. Moore, "All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast," Nat. Photonics 1(9), 526-530 (2007).
[CrossRef]

Niemeijer, M.

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

Pan, Z.

Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).

Prasad, M.

Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).

Soares, J.

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

Staal, J.

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

Tromberg, B.

Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).

van Ginneken, B.

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

Viergever, M.

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

IEEE Transactions on Medical Imaging (2)

J. Staal, M. Abramoff, M. Niemeijer, M. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Transactions on Medical Imaging 23(4), 501-509 (2004).
[CrossRef]

J. Soares, J. Leandro, R. Cesar, H. Jelinek, and M. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Transactions on Medical Imaging 25(9), 1214-1222 (2006).
[CrossRef]

IEEE Transactions on Pattern Analysis and Machine Intelligence (2)

Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1552-1560 (2003).

R. A. Jarvis, "A Perspective on Range Finding Techniques for Computer Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence 5(2), 122-139 (1983).
[CrossRef]

Nat. Photonics (1)

E. M. C. Hillman and A. Moore, "All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast," Nat. Photonics 1(9), 526-530 (2007).
[CrossRef]

Other (15)

H. D. Zeman, G. Lovhoiden, C. Vrancken, and R. K. Danish, "Prototype vein contrast enhancer," Opt. Eng. 44, 086,401 (2005).

V. C. Paquit, F. Meriaudeau, J. R. Price, and K. W. Tobin, "Simulation of skin reflectance images using 3D tissue modeling and multispectral Monte Carlo light propagation," in 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008. EMBS 2008, pp. 447-450 (2008).

V. C. Paquit, J. R. Price, R. Seulin, F. Meriaudeau, R. H. Farahi, J. Kenneth W. Tobin, and T. L. Ferrell, "Nearinfrared imaging and structured light ranging for automatic catheter insertion," Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display 6141(1), 61411T (pages 9) (2006).

V. C. Paquit, J. R. Price, F. Meriaudeau, J. Kenneth W. Tobin, and T. L. Ferrell, "Combining near-infrared illuminants to optimize venous imaging," Medical Imaging 2007: Visualization and Image-Guided Procedures 6509(1), 65090H (pages 9) (2007).

R. Anderson and J. Parrish, "The Optics of Human Skin," Journal of Investigative Dermatology (1981).
[CrossRef] [PubMed]

Z. Zhang, "Flexible Camera Calibration by Viewing a Plane from Unknown Orientations," IEEE International Conference on Computer Vision 1, 666 (1999).
[CrossRef]

V. C. Paquit, "Imagerie multispectrale et mod’elisation 3D pour l’estimation quantitative des vaisseaux sanguins sous cutan’es," Ph.D. thesis, Universit’e de Bourgogne, Le Creusot, France (2008).

E. M. C. Hillman, "Experimental and theoretical investigations of near infrared tomographic imaging methods and clinical applications," Ph.D. thesis, Department of Medical Physics and Bioengineering - University College London (2002).

J. Forest, J. M. Teixidor, J. Salvi, and E. Cabruja, "A Proposal for Laser Scanners Sub-pixel Accuracy Peak Detector," in Workshop on European Scientific and Industrial Collaboration, pp. 525-532 (Mickolj (Hungria), 2003).

P. E. Bezier, Emploi des machines a commande numerique (Masson et Cie., 1970). Translated by A. R. Forrest and A. F. Pankhurst as Numerical Control - Mathematics and Applications, (John Wiley and Sons, Ltd., London, 1972).

A. Efremov, V. Havran, and H.-P. Seidel, "Robust and numerically stable B’ezier clipping method for ray tracing NURBS surfaces," in SCCG ’05: Proceedings of the 21st spring conference on Computer graphics, pp. 127-135 (ACM, New York, NY, USA, 2005).
[CrossRef]

V. C. Paquit, F. Meriaudeau, J. R. Price, and K. W. Tobin, "Multispectral Imaging For Subcutaneous Structures Classification And Analysis," in International Topical Meeting on Optical Sensing and Artificial Vision, OSAV’2008, Saint Petersburg, Russia (2008).
[PubMed]

H. J. Noordmans, R. de Roode, and R. Verdaasdonk, "Compact multi-spectral imaging system for dermatology and neurosurgery," Proc. SPIE 6510, 65100I (2007).

K. Fukunaga, Statistical Pattern Recognition (Morgan Kaufmann, 1990).

C. Steger, "Extraction of curved lines from images," in Proceedings of the 13th International Conference on Pattern Recognition, Vol. 2, pp. 251-255 (1996).

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Figures (5)

Fig. 1.
Fig. 1.

Experimental setup

Fig. 2.
Fig. 2.

Triangulation principle

Fig. 3.
Fig. 3.

(a) image of the laser lines on the surface of the skin, (b) centerlines detected using a supbixel operator are in red, (c) Laser line on the forearm and (d) its 3D reconstruction.

Fig. 4.
Fig. 4.

Example of the masks used for the LDA process. (a) Manually generated 2 class mask. (b)Aumatically (based on the PCA and Steger Algorithm) generated 2 class mask (c) Manually generated 3 class mask. (d)Aumatically (based on the PCA and Steger Algorithm) generated 3 class mask

Fig. 5.
Fig. 5.

Comparison of the vascular centerline detection using Steger’s algorithm for different input features and class masks: (first column) two class problem - vein/not vein - where the mask is manually defined; (second column) two class problem with mask automatically generated from the PCA image; (third column) three class problem - vein/skin/other -with mask manually defined; and (fourth column) three class problem with mask automatically generated from the PCA image.

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