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Bayesian Differentiation of Multi-scale Line-Structures for Model-Free Instrument Segmentation in Thoracoscopic Images

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Image Analysis and Recognition (ICIAR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3656))

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Abstract

A reliable method to segment instruments in endoscope images is required as part of an enhanced reality system for minimally invasive surgery of the spine. Numerous characteristics of these images make typical intensity or model constraints for segmentation impractical. Rather, line-structure concepts are used to exploit the high length-to-diameter ratio expected of surgical instruments. A Bayesian selection scheme is proposed, and is shown to reliably differentiate these target objects from other line-like background structures.

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References

  1. Zhang, X., Payandeh, S.: Application of Visual Tracking for Robot Assisted Laparoscopic Surgery. J. Robotic Systems 19(7), 315–328 (2002)

    Article  MATH  Google Scholar 

  2. Caselles, V., Kimmel, R., Sapiro, G.: Geodesic Active Contours. Int. J. Computer Vision 22(1), 61–79 (1997)

    Article  MATH  Google Scholar 

  3. Leventon, M., Faugeras, O., Grimson, E., Wells, W.: Level Set Based Segmentation with Intensity and Curvature Priors. Mathematical Methods in Biomedical Image Analysis 2000 (2000)

    Google Scholar 

  4. Chan, T., Vese, L.: Active Contours Without Edges. IEEE Trans Image Pro 10(2), 266–277 (2001)

    Article  MATH  Google Scholar 

  5. Xie, X., Mirmehdi, M.: RAGS: Region-Aided Geometric Snake. IEEE Trans. Image Pro. 13(5), 640–652 (2004)

    Article  MathSciNet  Google Scholar 

  6. Leventon, M., Grimson, W., Faugeras, O.: Statistical Shape Influence in Geodesic Active Contours. In: Comp. Vision and Patt. Recon, CVPR (2000)

    Google Scholar 

  7. Chen, J., Amini, A.: Quantifying 3-D Vascular Structures in MRA Images Using Hybrid PDE and Geometric Deformable Models. IEEE Trans Medical Imaging 23(10), 1251–1262 (2004)

    Article  Google Scholar 

  8. Koller, T., Gerig, G., Szekely, G., Dettwiler, D.: Multiscale Detection of Curvilinear Structures in 2-D and 3-D Image Data. In: IEEE Proc. 5th Int’l. Conf. Comp. Vision, pp. 864–869 (1995)

    Google Scholar 

  9. Lorenz, C., Carlsen, I.-C., Buzug, T., Fassnacht, C., Weese, J.: Multi-scale Line Segmentation with Automatic Estimation of Width, Contrast and Tangential Direction in 2D and 3D Medical Images. In: Proc. 1st Int’l Joint Conf. CVRMed and MRCAS (CVRMed/MRCAS 1997), pp. 233–242 (1997)

    Google Scholar 

  10. Xu, C., Prince, J.L.: Snakes, Shapes, and Gradient Vector Flow. IEEE Transactions on Image Processing 7(3), 359–369 (1998)

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Ecole Polytechnique de Montreal, C.P. 6079, 53851 succ. Centre-ville, Montreal, H3C 3A7, Canada

    Luke Windisch & Farida Cheriet

  2. Department of Orthopaedics, Sainte Justine Hospital, Montreal, Canada

    Farida Cheriet & Guy Grimard

Authors
  1. Luke Windisch
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  2. Farida Cheriet
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  3. Guy Grimard
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Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

  2. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, P.O. Box, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2005 Springer-Verlag Berlin Heidelberg

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Windisch, L., Cheriet, F., Grimard, G. (2005). Bayesian Differentiation of Multi-scale Line-Structures for Model-Free Instrument Segmentation in Thoracoscopic Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_114

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  • DOI: https://doi.org/10.1007/11559573_114

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29069-8

  • Online ISBN: 978-3-540-31938-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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