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Extracting Curve Skeletons from Gray Value Images for Virtual Endoscopy

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Medical Imaging and Augmented Reality (MIAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5128))

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Abstract

The extraction of curve skeletons from tubular networks is a necessary prerequisite for virtual endoscopy applications. We present an approach for curve skeleton extraction directly from gray value images that supersedes the need to deal with segmentations and skeletonizations. The approach uses properties of the Gradient Vector Flow to derive a tube-likeliness measure and a medialness measure. Their combination allows the detection of tubular structures and an extraction of their medial curves that stays centered also in cases where the structures are not tubular such as junctions or severe stenoses. We present results on clinical datasets and compare them to curve skeletons derived with different skeletonization approaches from high quality segmentations. Our approach achieves a high centerline accuracy and is computationally efficient by making use of a GPU based implementation of the Gradient Vector Flow.

This work was supported by the Austrian Science Fund (FWF) under the doctoral program Confluence of Vision and Graphics W1209.

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References

  1. Palagyi, K., Sorantin, E., Balogh, E., Kuba, A., Halmai, C., Erdohelyi, B., Hausegger, K.: A sequential 3D thinning algorithm and its medical applications. In: Insana, M.F., Leahy, R.M. (eds.) IPMI 2001. LNCS, vol. 2082, pp. 409–415. Springer, Heidelberg (2001)

    Google Scholar 

  2. Hassouna, M.S., Farag, A.A.: On the extraction of curve skeletons using gradient vector flow. In: Proc. of ICCV, pp. 1–8 (2007)

    Google Scholar 

  3. Hassouna, M.S., Farag, A.A., Falk, R.: Differential fly-throughs (DFT): A general framework for computing flight paths. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 654–661. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  4. Bouix, S., Siddiqi, K., Tannenbaum, A.: Flux driven automatic centerline extraction. MIA 9(3), 209–221 (2005)

    Article  Google Scholar 

  5. Deschamps, T., Cohen, L.D.: Fast extraction of minimal paths in 3d images and applications to virtual endoscopy. MIA 5(4), 281–299 (2001)

    Article  Google Scholar 

  6. Wink, O., Niessen, W., Viergever, M.: Multiscale vessel tracking. IEEE TMI 21(2)23(1), 130–133 (2004)

    Google Scholar 

  7. Aylward, S., Bullit, E.: Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction. IEEE TMI 21(2), 61–75 (2002)

    Google Scholar 

  8. Krissian, K., Malandain, G., Ayache, N., Vaillant, R., Trousset, Y.: Model-based detection of tubular structures in 3D images. CVIU 2(80), 130–171 (2000)

    Google Scholar 

  9. Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale vessel enhancement filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)

    Google Scholar 

  10. Bullitt, E., Aylward, S., Smith, K., Jukherji, S., Jiroutek, M., Muller, K.: Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparision with x-ray angiograms. MIA 5(2), 157–169 (2001)

    Article  Google Scholar 

  11. Szymczak, A., Stillman, A., Tannenbaum, A., Mischaikow, K.: Coronary vessel trees from 3d imagery: A topological approach. MIA 10(4), 548–559 (2006)

    Article  Google Scholar 

  12. Bauer, C., Bischof, H.: A novel approach for detection of tubular objects and its application to medical image analysis. In: Proc. of DAGM 2008 (in print) (2008)

    Google Scholar 

  13. Xu, C., Prince, J.L.: Snakes, shapes, and gradient vector flow. IEEE TMI 7(3), 359–369 (1998)

    MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Institute for Computer Graphics and Vision, Graz University of Technology, Austria

    Christian Bauer & Horst Bischof

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  1. Christian Bauer
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  2. Horst Bischof
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Takeyoshi Dohi Ichiro Sakuma Hongen Liao

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© 2008 Springer-Verlag Berlin Heidelberg

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Bauer, C., Bischof, H. (2008). Extracting Curve Skeletons from Gray Value Images for Virtual Endoscopy. In: Dohi, T., Sakuma, I., Liao, H. (eds) Medical Imaging and Augmented Reality. MIAR 2008. Lecture Notes in Computer Science, vol 5128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79982-5_43

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  • DOI: https://doi.org/10.1007/978-3-540-79982-5_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79981-8

  • Online ISBN: 978-3-540-79982-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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