The Assessment of Brain Volume in the Postoperative Craniosynostosis

  • Anna Fabijańska
  • Jarosław Gocławski
  • Wanda Mikołajczyk-Wieczorek
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 283)


This paper considers the problem of brain volume assessment in children with craniosynostosis using the algorithms of image processing and analysis. In particular the postoperative craniosynostosis is considered. In this case the quantitative assessment of brain volume is very challenging due to missing fragments of the skull. These are removed during the corrective surgery and make image segmentation algorithms fail when applied to the brain extraction. The approach introduced in this paper overcomes this problem by combining morphological processing with the 3D random walk segmentation. The details of the introduced approach are explained in the paper contents. The results of the brain segmentation and brain volume assessment for the postoperative subjects are presented, analysed and discussed.


image segmentation brain volume assessment craniosynostosis random walker 


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  1. 1.
    Cohen, M.M., MacLean, R.E.: Craniosynostosis: Diagnosis, Evaluation, and Management. Oxford University Press, Oxford (2000)Google Scholar
  2. 2.
    David, D.J., Poswillo, D., Simpson, D.: The Craniosynostoses: Causes, Natural History, and Management. Springer (2013)Google Scholar
  3. 3.
    Elias de Oliveira, M., Hallila, H., Ritvanen, A., Buchler, P., Paulasto, M., Hukki, J.: Postoperative Evaluation of Surgery for Craniosynostosis Based on Image Registration Techniques. In: Proc. Ann. Int. Conf. Engineering in Medicine and Biology Society, pp. 5620–5623 (2010)Google Scholar
  4. 4.
    Elias de Oliveira, M., Hallila, H., Ritvanen, A., Buchler, P., Paulasto, M., Hukki, J.: Feature-Invariant Image Registration Method for Quantification of Surgical Outcomes in Patients with Craniosynostosis: a Preliminary Study. J. Pediatr. Surg. 46(10), E1–E8 (2011)Google Scholar
  5. 5.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice-Hall Inc. (2006)Google Scholar
  6. 6.
    Grady, L.: Random Walks for Image Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1768–1783 (2006)CrossRefGoogle Scholar
  7. 7.
    Hayward, R., Jones, B., Dunaway, D.: Clinical Management of Craniosynostosis. Mac Keith Press (2004)Google Scholar
  8. 8.
    Labatut, V., Cherifi, H.: Accuracy measures for the comparison of classifiers. CoRR, arXiv:1207.3790 (2012),
  9. 9.
    Lin, H.J., Ruiz-Correa, S., Sze, R.W., Cunningham, M.L., Speltz, M.L., Hing, A.V., Shapiro, L.G.: Efficient Symbolic Signatures for Classifying Craniosynostosis Skull Deformities. In: Liu, Y., Jiang, T.-Z., Zhang, C. (eds.) CVBIA 2005. LNCS, vol. 3765, pp. 302–313. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Mendoza, C.S., Safdar, N., Myers, E., Kittisarapong, T., Rogers, G.F., Linguraru, M.G.: Computer-Based Quantitative Assessment of Skull Morphology for Craniosynostosis. In: Drechsler, K., Erdt, M., Linguraru, M.G., Oyarzun Laura, C., Sharma, K., Shekhar, R., Wesarg, S. (eds.) CLIP 2012. LNCS, vol. 7761, pp. 98–105. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Paniagua, B., Emodi, O., Hill, J., Fishbaugh, J., Pimenta, L.A., Aylward, S.R., Andinet, E., Gerig, G., Gilmore, J., van Aalst, J.A., Styner, M.: 3D of Brain Shape and Volume After Cranial Vault Remodeling Surgery for Craniosynostosis Correction in Infants. In: Proc. SPIE, vol. 8672 (2013), doi:10.1117/12.2006524Google Scholar
  12. 12.
    Wolański, W., Larysz, D., Gzik, M., Kawlewska, E.: Modeling and Biomechanical Analysis of Craniosynostosis Correction with the Use of Finite Element Method. Int. J. Numer. Method. Biomed. Eng. 29(8), 916–925 (2013)CrossRefGoogle Scholar
  13. 13.
    Yang, S., Shapiro, L.G., Cunningham, M.L., Speltz, M., Le, S.: Classification and Feature Selection for Craniosynostosis. In: Proc. 2nd ACM Conf. Bioinformatics, Computational Biology and Biomedicine, pp. 340–344 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Anna Fabijańska
    • 1
  • Jarosław Gocławski
    • 1
  • Wanda Mikołajczyk-Wieczorek
    • 2
  1. 1.Institute of Applied Computer ScienceLodz University of TechnologyLodzPoland
  2. 2.Research InstitutePolish Mother’s Memorial HospitalLodzPoland

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