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Improving Diagnosis and Intervention: A Complete Approach for Registration of Liver CT Data

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Abdominal Imaging. Computational and Clinical Applications (ABD-MICCAI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7029))

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Abstract

Registration of liver CT scans from different points in time or different phases of contrast agent saturation is a highly demanded tool for computer aided diagnosis, operation planning and intervention. This work presents a complete registration workflow to precisely overlap scans from 4 different application scenarios including registration of pre-treatment and post-treatment data as well as registration of multi-phase CT. Various state of the art techniques in shape modeling and matching, visualization as well as augmented interaction are applied to cover all of the described scenarios in a clinically usable system. Our system has been in use for clinical evaluation under real life conditions and has been tested on more than 30 patients.

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References

  1. Drechsler, K., Oyarzun Laura, C.: Hierachical decomposition of vessel skeletons for graph creation and feature extraction. In: Proc. BIBM (2010)

    Google Scholar 

  2. Drechsler, K., Oyarzun Laura, C.: A novel multiscale integration approach for vessel enhancement. In: IEEE CBMS, pp. 92–97 (2010)

    Google Scholar 

  3. Drechsler, K., Oyarzun Laura, C., Chen, Y., Erdt, M.: Semi-automatic anatomical tree matching for landmark-based elastic registration of liver volumes. Journal of Healthcare Engineering 1(1), 101–123 (2010)

    Article  Google Scholar 

  4. Erdt, M., Kirschner, M., Steger, S., Wesarg, S.: Fast automatic liver segmentation combining learned shape priors with observed shape deviation. In: IEEE CBMS, pp. 249–254 (2010)

    Google Scholar 

  5. Erdt, M., Schlegel, P., Wesarg, S.: Multi-layer deformable models for medical image segmentation. In: IEEE ITAB, p. 4 (2010)

    Google Scholar 

  6. Graham, M.W., Higgins, W.E.: Globally optimal model-based matching of anatomical trees. In: Medical Imaging: Image Processing, vol. 6144 (2006)

    Google Scholar 

  7. Heimann, T., van Ginneken, B., Styner, M., et al.: Comparison and Evaluation of Methods for Liver Segmentation from CT datasets. IEEE Trans. Med. Imaging 28(8), 1251–1265 (2009)

    Article  Google Scholar 

  8. Metzen, J.H., Kröger, T., Schenk, A., Zidowitz, S., Peitgen, H.-O., Jiang, X.: Matching of Tree Structures for Registration of Medical Images. In: Escolano, F., Vento, M. (eds.) GbRPR. LNCS, vol. 4538, pp. 13–24. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Oyarzun Laura, C., Drechsler, K.: Computer assisted matching of anatomical vessel trees. Computers & Graphics 35(2), 299–311 (2011)

    Article  Google Scholar 

  10. Tschirren, J., McLennan, G., Palágyi, K., Hoffman, E.A., Sonka, M.: Matching and anatomical labeling of human airway tree. IEEE Trans. Med. Imaging 24(12), 1540–1547 (2005)

    Article  Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Erdt, M., Oyarzun Laura, C., Drechsler, K., De Beni, S., Solbiati, L. (2012). Improving Diagnosis and Intervention: A Complete Approach for Registration of Liver CT Data. In: Yoshida, H., Sakas, G., Linguraru, M.G. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2011. Lecture Notes in Computer Science, vol 7029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28557-8_14

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  • DOI: https://doi.org/10.1007/978-3-642-28557-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28556-1

  • Online ISBN: 978-3-642-28557-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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