Contour-Based TVUS-MR Image Registration for Mapping Small Endometrial Implants

  • Amir Yavariabdi
  • Chafik Samir
  • Adrien Bartoli
  • David Da Ines
  • Nicolas Bourdel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8198)


We propose a multi-modal image registration and fusion method to cope with the limitations of Magnetic Resonance (MR) and Transvaginal Ultrasound (TVUS) imaging in observing abdominal endometrial implants. Our method facilitates the transfer of two types of information from a 2D TVUS image to a 2D MR slice: (1) the location and shape of small implants and (2) the implants’ depth of infiltration in the host tissue. Our registration method uses contour correspondences through a novel variational one-step deformable Iterative Closest Point (ICP) method. The proposed method compared favorably with classical ICP and Thin-Plate Spline Robust Point Matching (TPS-RPM) on several datasets.


Contour-based image registration fusion endometriosis localization 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Castellani, U., Bartoli, A.: 3D Shape Registration. In: 3D Imaging, Analysis, and Applications (2012)Google Scholar
  2. 2.
    Modersitzki, J.: Numerical Methods for Image Registration. Oxford University Press (2004)Google Scholar
  3. 3.
    Modersitzki, J.: Flexible Algorithms for Image Registration. SIAM (2009)Google Scholar
  4. 4.
    Sotiras, A., Davatzikos, C., Paragios, N.: Deformable Medical Image Registration: A Survey. In: TMI, pp. 1153–1190. IEEE Press, New York (2013)Google Scholar
  5. 5.
    Amberg, B., Romdhani, S., Vetter, T.: Optimal Step Nonrigid ICP Algorithm for Surface Registration. In: CVPR (2007)Google Scholar
  6. 6.
    Chamie, L.P., Blasbalg, R., Pereira, R.M.A., Warmbrand, G., Serafini, P.C.: Findings of Pelvic Endometriosis at Transvaginal US, MR Imaging, and Laproscopy. RadioGraphics 31, 71–100 (2011)CrossRefGoogle Scholar
  7. 7.
    Brosens, I., Puttemans, P., Campo, R., Gordts, S., Kinkel, K.: Diagnosis of Endometriosis: Pelvic Endoscopy and Imaging Techniques. Best Practice and Research Clinical Obstetrics and Gynaecology 18, 285–303 (2004)CrossRefGoogle Scholar
  8. 8.
    Yavariabdi, A., Samir, C., Bartoli, A., Da Ines, D., Bourdel, N.: Mapping Endometrial Implants by 2D/2D Registration of TVUS to MR Images from Point Correspondences. In: ISBI (2013)Google Scholar
  9. 9.
    Mitra, J., Oliver, A., Marti, R., Llado, X., Vilanova, J.C.: Multimodal Prostate Registration using Thin-Plate Splines from Automatic Correspondences. Digital Image Computing: Techniques and Applications (2010)Google Scholar
  10. 10.
    Cosse, A.: Diffeomorphic Surface-based Registration for MR-US Fusion in Prostate Brachytherapy. In: MELECON, pp. 903–907 (2012)Google Scholar
  11. 11.
    Reynier, C., Troccaz, J., Fourneret, P., Dusserre, A., Gayjeune, C., Descotes, J., Bolla, M., Giraud, J.: MRI/TRUS data fusion for prostate brachytherapy. Preliminary results. Medical Physics 31, 1568–1575 (2004)CrossRefGoogle Scholar
  12. 12.
    Fitzgibbon, A.W., Levoy, M.: Robust Registration of 2D and 3D Point Sets. Image and Vision Computing, 1145–1153 (2003)Google Scholar
  13. 13.
    Chui, H., Rangarajan, A.: A New Point Matching Algorithm for Non-Rigid Registration. CVIU 89, 114–141 (2003)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Amir Yavariabdi
    • 1
  • Chafik Samir
    • 1
  • Adrien Bartoli
    • 1
  • David Da Ines
    • 1
  • Nicolas Bourdel
    • 1
  1. 1.ISIT UMR 6284 CNRSUniversité d’AuvergneClermont-FerrandFrance

Personalised recommendations