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Registration Evaluation by De-enhancing CT Images

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Biomedical Image Registration (WBIR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10883))

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Image registration is relevant for many medical procedures. For CT-guided ablation procedures, integrating the lesion location from diagnostic contrast-enhanced CT (CECT) images in interventional CT images may provide better guidance for the interventional radiologist. The main requirement for such methods is to accurately align the lesion location. This, in general, can not be measured, and often surrogates are used for the assessment. In this work, we present a method that permits the assessment of the accuracy of the lesion localization, i.e. assessing the value that is relevant for clinical practice. To this end, we developed a method that virtually removes the contrast agent from an interventional CT image, use this image for the registration, and use the original CECT image for the assessment. For the experimental evaluation, imaging data of 20 subjects (33 lesions) were used, and the registration accuracy of a publicly available registration method was assessed using this method.

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  1. Fischer, B., Modersitzki, J.: Ill-posed medicine-an introduction to image registration. Inverse Prob. 24, 034008 (2008)

    Article  MathSciNet  Google Scholar 

  2. Rohlfing, T.: Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable. IEEE Trans. Med. Imaging. 31(2), 153–163 (2012)

    Article  Google Scholar 

  3. Luu, H.M., Klink, C., Niessen, W., Moelker, A., van Walsum, T.: An automatic registration method for pre- and post-interventional CT images for assessing treatment success in liver RFA treatment. Med. Phys. 42(9), 5559–5567 (2015)

    Article  Google Scholar 

  4. Luu, H.M., Klink, C., Niessen, W., Moelker, A., Walsum, T.V.: Non-rigid registration of liver CT images for CT-guided ablation of liver tumors. PLOS ONE 11(9), e0161600 (2016)

    Article  Google Scholar 

  5. Laura, C., Drechsler, K., Wesarg, S., Bale, R.: Accurate physics-based registration for the outcome validation of minimal invasive interventions and open liver surgeries. IEEE Trans. Biomed. Eng. PP(99), 1 (2016)

    Google Scholar 

  6. Rieder, C., Wirtz, S., Strehlow, J., Zidowitz, S., Bruners, P., Isfort, P., Mahnken, A.H., Peitgen, H.O.: Automatic alignment of pre- and post-interventional liver CT images for assessment of radiofrequency ablation, vol. 8316, pp. 83163E–83163E-8 (2012)

    Google Scholar 

  7. Wang, B., Ying, C.A.O.: Liver medical image registration based on biomechanical model. Multimed. Tools Appl. 76, 1–18 (2016)

    Google Scholar 

  8. Nielsen, M.S., Østergaard, L.R., Carl, J.: A new method to validate thoracic CT-CT deformable image registration using auto-segmented 3D anatomical landmarks. Acta Oncol. 54(9), 1515–1520 (2015)

    Article  Google Scholar 

  9. Nie, K., Chuang, C., Kirby, N., Braunstein, S., Pouliot, J.: Site-specific deformable imaging registration algorithm selection using patient-based simulated deformations. Med. Phys. 40(4), 041911 (2013)

    Article  Google Scholar 

  10. Klein, S., Staring, M., Murphy, K., Viergever, M., Pluim, J.P.W.: Elastix: a toolbox for intensity-based medical image registration. IEEE Trans. Med. Imaging 29(1), 196–205 (2010)

    Article  Google Scholar 

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Theo van Walsum was supported by ITEA project 13031: Benefit.

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Correspondence to Theo van Walsum .

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Luu, M.H., Boulkhrif, H., Moelker, A., van Walsum, T. (2018). Registration Evaluation by De-enhancing CT Images. In: Klein, S., Staring, M., Durrleman, S., Sommer, S. (eds) Biomedical Image Registration. WBIR 2018. Lecture Notes in Computer Science(), vol 10883. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92257-7

  • Online ISBN: 978-3-319-92258-4

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