Abstract
The success of craniomaxillofacial (CMF) surgery depends not only on the surgical techniques, but also upon an accurate surgical planning. However, surgical planning for CMF surgery is challenging due to the absence of a patient-specific reference model. In this paper, we present a method to automatically estimate an anatomically correct reference shape of jaws for the patient requiring orthognathic surgery, a common type of CMF surgery. We employ the sparse representation technique to represent the normal regions of the patient with respect to the normal subjects. The estimated representation is then used to reconstruct a patient-specific reference model with “restored” normal anatomy of the jaws. We validate our method on both synthetic subjects and patients. Experimental results show that our method can effectively reconstruct the normal shape of jaw for patients. Also, a new quantitative measurement is introduced to quantify the CMF deformity and validate the method in a quantitative approach, which is rarely used before.
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Xia, J.J., Gateno, J., Teichgraeber, J.F.: New clinical protocol to evaluate craniomaxillofacial deformity and plan surgical correction. J. Oral Maxillofac. Surg. 67(10), 2093–2106 (2009)
Zhang, S., Zhan, Y., Dewan, M., Huang, J., Metaxas, D.N., Zhou, X.S.: Towards robust and effective shape modeling: Sparse shape composition. Medical Image Analysis 16(1), 265–277 (2012)
Starck, J.L., Elad, M., Donoho, D.L.: Image decomposition via the combination of sparse representations and a variational approach. IEEE Transactions on Image Processing 14(10), 1570–1582 (2005)
Donoho, D.L.: For most large underdetermined systems of linear equations the minimal 1-norm solution is also the sparsest solution. Communications on Pure and Applied Mathematics 59(6), 797–829 (2006)
Blanz, V., Mehl, A., Vetter, T., Seidel, H.P.: A statistical method for robust 3d surface reconstruction from sparse data. In: Proceedings of the 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 3DPVT 2004, pp. 293–300. IEEE (2004)
Yokota, F., Okada, T., Takao, M., Sugano, N., Tada, Y., Tomiyama, N., Sato, Y.: Automated CT segmentation of diseased hip using hierarchical and conditional statistical shape models. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013, Part II. LNCS, vol. 8150, pp. 190–197. Springer, Heidelberg (2013)
Zachow, S., Lamecker, H., Elsholtz, B., Stiller, M.: Reconstruction of mandibular dysplasia using a statistical 3d shape model. In: International Congress Series, vol. 1281, pp. 1238–1243. Elsevier (2005)
Swennen, G.R., Schutyser, F.A., Hausamen, J.E.: Three-dimensional cephalometry: a color atlas and manual. Springer (2005)
Xia, J.J., McGrory, J.K., Gateno, J., Teichgraeber, J.F., Dawson, B.C., Kennedy, K.A., Lasky, R.E., English, J.D., Kau, C.H., McGrory, K.R.: A new method to orient 3-dimensional computed tomography models to the natural head position: a clinical feasibility study. J. Oral Maxillofac. Surg. 69(3), 584–591 (2011)
Tibshirani, R.: Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological), 267–288 (1996)
Bookstein, F.L.: Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Trans. on Pattern Analysis and Machine Intelligence 11(6), 567–585 (1989)
Wang, L., et al.: Automated segmentation of CBCT image using spiral CT atlases and convex optimization. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013, Part III. LNCS, vol. 8151, pp. 251–258. Springer, Heidelberg (2013)
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Ren, Y. et al. (2014). Estimating Anatomically-Correct Reference Model for Craniomaxillofacial Deformity via Sparse Representation. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8674. Springer, Cham. https://doi.org/10.1007/978-3-319-10470-6_10
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DOI: https://doi.org/10.1007/978-3-319-10470-6_10
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