Abstract
Many image-based systems for aiding the surgeon during minimally invasive surgery require the endoscopic camera to be calibrated at all times. This article proposes a method for accomplishing this goal whenever the camera has optical zoom and the focal length changes during the procedure. Our solution for online calibration builds on recent developments in tracking salient points using differential image alignment, is well suited for continuous operation, and makes no assumptions about the camera motion or scene rigidity. Experimental validation using both a phantom model and in vivo data shows that the method enables accurate estimation of focal length when the zoom varies, avoiding the need to explicitly recalibrate during surgery. To the best of our knowledge this the first work proposing a practical solution for online zoom calibration in the operation room.
Miguel Lourenço and João Barreto want to thank QREN-Mais Centro by generous funding through Novas Tecnologias para apoio à Saúde e Qualidade de Vida, Projecto A- Cirurgia e Diagnóstico Assistido por Computador Usando Imagem and the Portuguese Science Foundation by funding through grant SFRH/BD/63118/2009.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Melo, R., Barreto, J., Falcao, G.: A New Solution for Camera Calibration and Real-Time Image Distortion Correction in Medical Endoscopy-Initial Technical Evaluation. IEEE Transactions on Biomedical Engineering 59, 634–644 (2012)
Burschka, D., Li, M., Taylor, R., Hager, G.: Scale-Invariant Registratiou of Monocular Endoscopic Images to CT-Scans for Sinus Surgery. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3217, pp. 413–421. Springer, Heidelberg (2004)
Yamaguchi, T., et al.: Camera Model and Calibration Procedure for Oblique-Viewing Endoscope. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2879, pp. 373–381. Springer, Heidelberg (2003)
Stoyanov, D., Darzi, A., Yang, G.Z.: Laparoscope Self-calibration for Robotic Assisted Minimally Invasive Surgery. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 114–121. Springer, Heidelberg (2005)
Stewenius, H., Nister, D., Kahl, F., Schaffalitzky, F.: A minimal solution for relative pose with unknown focal length. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 789–794 (2005)
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press (2004) ISBN: 0521540518
Lee, T.Y., et al.: Automatic distortion correction of endoscopic images captured with wide-angle zoom lens. IEEE Transactions on Biomedical Engineering 60, 2603–2613 (2013)
Lourenço, M., Barreto, J.P.: Tracking Feature Points in Uncalibrated Images with Radial Distortion. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part IV. LNCS, vol. 7575, pp. 1–14. Springer, Heidelberg (2012)
Fitzgibbon, A.: Simultaneous linear estimation of multiple view geometry and lens distortion. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 125–132 (2001)
Baker, S., Matthews, I.: Lucas-kanade 20 years on: A unifying framework. International Journal of Computer Vision 56, 221–255 (2004)
Nister, D.: An efficient solution to the five-point relative pose problem. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 756–770 (2004)
Lourenco, M., Barreto, J., Vasconcelos, F.: sRD-SIFT: Keypoint Detection and Matching in Images With Radial Distortion. IEEE Transactions on Robotics 28, 752–760 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Lourenço, M., Barreto, J.P., Fonseca, F., Ferreira, H., Duarte, R.M., Correia-Pinto, J. (2014). Continuous Zoom Calibration by Tracking Salient Points in Endoscopic Video. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8673. Springer, Cham. https://doi.org/10.1007/978-3-319-10404-1_57
Download citation
DOI: https://doi.org/10.1007/978-3-319-10404-1_57
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10403-4
Online ISBN: 978-3-319-10404-1
eBook Packages: Computer ScienceComputer Science (R0)