Skip to main content
SpringerLink
Log in

Detection and correction of specular reflections for automatic surgical tool segmentation in thoracoscopic images

  • Original Paper
  • Published:
Machine Vision and Applications Aims and scope Submit manuscript

Abstract

This paper presents an algorithm that automatically detects and corrects specular reflections in thoracoscopic images and its application in the context of automatic segmentation of surgical tools. The detection is done by isolating the spike component of the specular reflection which is characterized by a bump at the end of the histogram of thoracoscopic images. The specular lobe is then extracted in the neighborhood of the spike component of the reflection. The result is a mask of the reflections positions in the image. Thereafter, the image is corrected using Oliveira et al.’s digital inpainting method. The automatic segmentation of surgical tools using the corrected images is then demonstrated. Results of the segmentation with and without the specular reflection elimination technique are compared. Moreover, 108 images extracted from 5 different surgeries performed under various conditions were considered to demonstrate the effectiveness of the proposed technique.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bertalmio, M., Sapiro, G., Caselles, V., Ballester, C.: Image inpainting. In: Akeley, K. (Ed.) Siggraph 2000, Computer Graphics Proceedings, pp. 417–424. ACM Press/ACM SIGGRAPH/Addison-Wesley Longman (2000). http://citeseer.ist.psu.edu/bertalmio00image.html

  2. Bochko, V., Miyake, Y.: Highlight removal in endoscope images. In: Proceedings of CGIV, pp. 167–171 (2006)

  3. Boisvert, J., Cheriet, F., Grimard, G.: Segmentation of laparoscopic images for computer assisted surgery. In: Image Analysis, 13th Scandinavian Conference, SCIA 2003, pp. 587–594 (16 June–2 July 2003)

  4. Deng Y. and Manjunath B. (2001). Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. Pattern Anal. Mach. Intell. 23(8): 800–810

    Article  Google Scholar 

  5. Donoho D.L. and Johnstone I.M. (1994). Ideal spatial adaptation by wavelet shrinkage. Biometrika 81(3): 425–455

    Article  MathSciNet  MATH  Google Scholar 

  6. Thongtrangan I., Le H. and Park J. (2004). Minimally invasive spinal surgery: a historical perspective. Neurosurg. Focus 16(1): E13

    Article  Google Scholar 

  7. Lin, S.: Generation of diffuse and specular appearance from photometric images. In: Workshop on Photometric Modeling for Computer Vision and Graphics, pp. 39–46 (1999)

  8. Ma, K.K., Wang, J.: Color distance histogram: a novel descriptor for color image segmentation. In: Proceedings of International Conference on Control, Automation, Robotics and Vision, vol. 3, pp. 1228–1232 (2002)

  9. Mallat S. (1999). A Wavelet Tour of Signal Processing. Academic, San Diego

    MATH  Google Scholar 

  10. Masnou, S.: Disocclusion: a variational approach using level lines. In: IEEE Transactions on Image Processing, vol. 11, Issue 2, pp. 68–76 (2002)

  11. Masnou, S., Morel, J.: Level lines based disocclusion. In: International Conference on Image Processing, vol. 3, pp. 259–263 (1998). http://citeseer.ist.psu.edu/masnou98level.html

  12. Okatani, T., Deguchi, K.: Reconstructing shape from shading with a point light source at the projection center: shape reconstruction from an endoscope image. In: Pattern Recognition, Proceedings of the 13th International Conference on, vol. 1, pp. 830–834 (25–29 August 1996)

  13. Oliveira, M., Bowen, B., McKenna, R., Chang, Y.: Fast digital image inpainting. In: Proceedings of the International Conference on Visualization, Imaging and Image Processing, pp. 261–266 (2001)

  14. Park, J.B.: Detection of specular highlights in color images using a new color space transformation. In: Proceedings of IEEE International Conference on Robotics and Biomimetics, pp. 737–41 (2004)

  15. Shafer S.A. (1985). Using color to separate reflection components. COLOR Res. Appl. 10(4): 210–218

    Article  Google Scholar 

  16. Torres, F., Angulo, J., Ortiz, F.: Automatic detection of specular reflectance in colour images using the ms diagram. In: Lecture Notes in Computer Science, vol. 2756, pp. 132–139 (2003)

  17. Vapnik V. (1995). The Nature of Statistical Learning Theory. Springer, Heidelberg

    MATH  Google Scholar 

  18. Vogt, F., Paulus, D., Heigl, B., et al.: Making the invisible visible: highlight substitution by color light fields. In: Proceedings of the First European Conference on Colour in Graphics, Imaging, and Vision, pp. 352–357 (2002)

  19. Windish, L., Cheriet, F., Grimard, G.: Bayesian differentiation of multi-scale line-structures for model-free instrument segmentation in thoracoscopic images. In: Kamel, M., Ampilho, A. (Eds.) Second International Conference ICIAR 2005, pp. 938–948. LNCS, vol. 3656 (2005)

  20. Wolff, L.B.: On the relative brightness of specular and diffuse reflection. In: Proceedings of CVPR, pp. 369–376 (1994)

  21. Xu, S.C., Ye, X., Wu, Y., Zhang, S.: Highlight detection and removal based on chromaticity. In: Proceedings of ICIAR 2005, pp. 199–206 (2005)

Download references

Author information

Authors and Affiliations

  1. École Polytechnique de Montréal, C.P. 6079, succ. Centre-Ville, Montreal, Canada, H3C 3A7

    Charles-Auguste Saint-Pierre, Jonathan Boisvert & Farida Cheriet

  2. Hôpital Sainte-Justine, 3175 Chemin de la Côte-Sainte-Catherine, Montreal, Canada, H3T 1C5

    Guy Grimard

Authors
  1. Charles-Auguste Saint-Pierre
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jonathan Boisvert
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guy Grimard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Farida Cheriet
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jonathan Boisvert.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Saint-Pierre, CA., Boisvert, J., Grimard, G. et al. Detection and correction of specular reflections for automatic surgical tool segmentation in thoracoscopic images. Machine Vision and Applications 22, 171–180 (2011). https://doi.org/10.1007/s00138-007-0099-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00138-007-0099-6

Keywords

Search

Navigation