Skip to main content
SpringerLink
Log in
Book cover

Mediterranean Conference on Medical and Biological Engineering and Computing

MEDICON 2019: XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 pp 312–321Cite as

Shift-Compensated Volumetric Interpolation of Tomographic Sequences for Accurate 3D Reconstruction

  • Conference paper
  • First Online:

  • 123 Accesses

Part of the book series: IFMBE Proceedings ((IFMBE,volume 76))

Abstract

In patients affected by craniosynostosis, i.e. a congenital cranial defect, diagnostic evaluation for a prompt surgical treatment is performed using low-dose three-dimensional computer tomography (CT), characterized by a poor spatial resolution (in terms of slice thickness). The limited number of CT images reduces the accuracy of the 3D reconstruction of the skull and leads to a coarser segmentation and modelling. In this paper, Motion Compensated Frame Interpolation (MCFI) techniques are applied for an effective axial interpolation of tomographic images sequences, with the main objective of obtaining a refined 3D reconstruction. The performance of the proposed method was assessed by using high-resolution CT sequences. After downsampling along the axial direction, the missing slices were recovered by using the proposed algorithm, to obtain an estimate of the original sequence. The experimental results show that the 3D models obtained from the downsampled/interpolated sequence are very close to those obtained from the original one thus providing a high-quality 3D skull reconstruction.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Nagaraja, S., Anslow, P., Winter, B.: Craniosynostosis. Clin. Radiol. 68(3), 284–292 (2013)

    Article  Google Scholar 

  2. Vannier, M.W., Hildebolt, C.F., Marsh, J.L., Pilgram, T.K., McAlister, W.H., Shackelford, G.D., Offutt, C.J., Knapp, R.H.: Craniosynostosis: diagnostic value of three-dimensional CT reconstruction. Radiology 173(3), 669–673 (1989)

    Article  Google Scholar 

  3. Kutanzi, K.R., Lumen, A., Koturbash, I., Miousse, I.R.: Pediatric exposures to ionizing radiation: carcinogenic considerations. Int. J. Environ. Res. Public Health 13 (2016)

    Article  Google Scholar 

  4. Bahreyni Toossi, M.T., Malekzadeh, M.: Radiation dose to newborns in neonatal intensive care units. Iran. J. Radiol. 9(3), 145–149 (2012)

    Article  Google Scholar 

  5. Volpe, Y., Furferi, R., Governi, L., Uccheddu, F., Carfagni, M., Mussa, F., Scagnet, M., Genitori, L.: Surgery of complex craniofacial defects: a single-step AM-based methodology. Comput. Methods Programs Biomed. 165, 225–233 (2018)

    Article  Google Scholar 

  6. Binaghi, S., Gudinchet, F., Rilliet, B.: Three-dimensional spiral CT of craniofacial malformations in children. Pediatr. Radiol. 30(12), 856–860 (2000)

    Article  Google Scholar 

  7. Raya, S.P., Udupa, J.K.: Shape-based interpolation of multidimensional objects. IEEE Trans. Med. Imaging 9(1), 32–42 (1990)

    Article  Google Scholar 

  8. Joliot, M., Mazoyer, B.M.: Three-dimensional segmentation and interpolation of magnetic resonance brain images. IEEE Trans. Med. Imaging 12(2), 269–277 (1993)

    Article  Google Scholar 

  9. Krishnamurthy, R., Woods, J.W., Moulin, P.: Frame interpolation and bidirectional prediction of video using compactly-encoded optical flow fields and label fields. IEEE Trans. Circuits Syst. Video Technol. 9(5), 713–726 (1997)

    Article  Google Scholar 

  10. Choi, B., Member, S., Han, J., Member, S.: Motion-compensated frame interpolation using bilateral motion estimation and adaptive overlapped block motion compensation. IEE Circuits Syst. Video Technol. 17(4), 407–416 (2007)

    Article  Google Scholar 

  11. Dikbas, S., Altunbasak, Y.: Novel true-motion estimation algorithm and its application to motion-compensated temporal frame interpolation. IEE Trans. Image Process. 22(8), 2931–2945 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  12. Kim, D., Lim, H., Park, H.: Iterative true motion estimation for motion-compensated frame interpolation. IEEE Trans. Circuits Syst. Video Technol. 23(3), 445–454 (2013)

    Article  Google Scholar 

  13. Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artif. Intell. 17(1–3), 185–203 (1981)

    Article  Google Scholar 

  14. Ertuk, S.: A new perspective to block motion estimation for video compression: high-frequency component matching. IEEE Signal Process. Lett. 14(2), 113–116 (2007)

    Article  Google Scholar 

  15. Puri, A., Hang, H.-M., Schilling, D.: An efficient block-matching algorithm for motion-compensated coding. In: Proceedings of ICASSP, pp. 1063–1066 (1987)

    Google Scholar 

  16. Young, R.W., Kingsbury, N.G.: Frequency-domain motion estimation using a complex lapped transform. IEEE Trans. Image Process. 2(1), 2–17 (1993)

    Article  Google Scholar 

  17. Pingault, M., Pellerin, D.: Motion estimation of transparent objects in the frequency domain. Signal Process. 84(4), 709–719 (2004)

    Article  MATH  Google Scholar 

  18. Huang, A.-M., Nguyen, T.Q.: A multistage motion vector processing method for motion-compensated frame interpolation. IEEE Trans. Image Process. 17(5), 694–708 (2008)

    Article  MathSciNet  Google Scholar 

  19. Goshtasby, A., Turner, D.A., Ackerman, L.V.: Matching of tomographic slices for interpolation. IEEE Trans. Med. Imaging 11(4), 507–516 (1992)

    Article  Google Scholar 

  20. Penney, G.P., Schnabel, J.A., Rueckert, D., Viergever, M.A., Niessen, W.J.: Registration-based interpolation. IEEE Trans. Med. Imaging 23(7), 922–926 (2004)

    Article  Google Scholar 

  21. Grevera, G.J., Udupa, J.K.: An objective comparison of 3-D image interpolation methods. IEEE Trans. Med. Imaging 17(4), 642–652 (1998)

    Article  Google Scholar 

  22. Leng, J., Xu, G., Zhang, Y.: Medical image interpolation based on multi-resolution registration. Comput. Math Appl. 66(1), 1–18 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  23. Horváth, A., Pezold, S., Weigel, M., Parmar, K., Cattin, P.: High order slice interpolation for medical images. In: Tsaftaris, S., Gooya, A., Frangi, A., Prince, J. (eds.) Simulation and Synthesis in Medical Imaging, SASHIMI 2017, Lecture Notes in Computer Science, vol. 10557. Springer, Cham (2017)

    Chapter  Google Scholar 

  24. Hinkle, J., Szegedi, M., Wang, B., Salter, B., Joshi, S.: 4D CT image reconstruction with diffeomorphic motion model. Med. Image Anal. 16(6), 1307–1316 (2012)

    Article  Google Scholar 

  25. Ehrhardt, J., Werner, R., Säring, D., Frenzel, T., Lu, W., Low, D., Handels, H.: An optical flow based method for improved reconstruction of 4D CT data sets acquired during free breathing. Med. Phys. 34(2), 21–711 (2007)

    Article  Google Scholar 

  26. Alparone, L., Barni, M., Bartolini, F., Cappellini, V.: Adaptively weighted vector-median filters for motion-fields smoothing. In: Proceedings of ICASSP, pp. 2267–2270 (1996)

    Google Scholar 

  27. Alparone, L., Barni, M., Bartolini, F., Caldelli, R.: Regularization of optic flow estimates by means of weighted vector median filtering. IEEE Trans. Image Process. 8(10), 1462–1467 (1999)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Engineering, University of Florence, Florence, Italy

    Chiara Santarelli, Fabrizio Argenti & Luciano Alparone

  2. Department of Industrial Engineering, University of Florence, Florence, Italy

    Francesca Uccheddu, Monica Carfagni & Lapo Governi

Authors
  1. Chiara Santarelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francesca Uccheddu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fabrizio Argenti
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Luciano Alparone
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Monica Carfagni
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lapo Governi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chiara Santarelli .

Editor information

Editors and Affiliations

  1. University of Coimbra, Coimbra, Portugal

    Jorge Henriques

  2. Universidade do Minho, Braga, Portugal

    Nuno Neves

  3. University of Coimbra, Coimbra, Portugal

    Paulo de Carvalho

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Santarelli, C., Uccheddu, F., Argenti, F., Alparone, L., Carfagni, M., Governi, L. (2020). Shift-Compensated Volumetric Interpolation of Tomographic Sequences for Accurate 3D Reconstruction. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-31635-8_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31634-1

  • Online ISBN: 978-3-030-31635-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation