Abstract
In this paper, we introduce a method for estimating patient-specific reference bony shape models for planning of reconstructive surgery for patients with acquired craniomaxillofacial (CMF) trauma. We propose an automatic bony shape estimation framework using pre-traumatic portrait photographs and post-traumatic head computed tomography (CT) scans. A 3D facial surface is first reconstructed from the patient’s pre-traumatic photographs. An initial estimation of the patient’s normal bony shape is then obtained with the reconstructed facial surface via sparse representation using a dictionary of paired facial and bony surfaces of normal subjects. We further refine the bony shape model by deforming the initial bony shape model to the post-traumatic 3D CT bony model, regularized by a statistical shape model built from a database of normal subjects. Experimental results show that our method is capable of effectively recovering the patient’s normal facial bony shape in regions with defects, allowing CMF surgical planning to be performed precisely for a wider range of defects caused by trauma.
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References
Xia, J., et al.: Algorithm for planning a double-jaw orthognathic surgery using a computer-aided surgical simulation (CASS) protocol. Part 2: three-dimensional cephalometry. Int. J. Oral Maxillofac. Surg. 44(12), 1441–1450 (2015)
Gellrich, N.C., et al.: Computer assisted oral and maxillofacial reconstruction. J. Comput. Inf. Technol. 14(1), 71–77 (2006)
Anton, F.M., et al.: Virtual reconstruction of bilateral midfacial defects by using statistical shape modeling. J. Oral Maxillofac. Surg. 47(7), 1054–1059 (2019)
Heimann, T., Meinzer, H.: Statistical shape models for 3D medical image segmentation: a review. Med. Imag. Anal. 13(4), 543–563 (2009)
Wang, L., et al.: Estimating patient-specific and anatomically correct reference model for craniomaxillofacial deformity via sparse representation. Med. Phys. 42(10), 5809–5816 (2015)
Xie, S., Leow, W.K., Lim, T.C.: Laplacian deformation with symmetry constraints for reconstruction of defective skulls. In: Felsberg, M., Heyden, A., Krüger, N. (eds.) CAIP 2017. LNCS, vol. 10425, pp. 24–35. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-64698-5_3
Sorkine, O., et al.: Laplacian surface editing. In: Proceedings of Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, pp. 175–184 (2004)
Donoho, D.L.: For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution. Commun. Pure Appl. Math. 59(6), 797–829 (2006)
Bulat, A., Tzimiropoulos, G.: How far are we from solving the 2D & 3D face alignment problem? (and a dataset of 230,000 3D facial landmarks). In: Proceedings of IEEE International Conference on Computer Vision, vol. 1, p. 8 (2017)
Blanz, V., Vetter, T.: Face recognition based on fitting a 3D morphable model. IEEE Trans. Pattern Anal. Mach. Intell. 25(9), 1063–1074 (2003)
Piotraschke, M., Blanz, V.: Automated 3D face reconstruction from multiple images using quality measures. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 3418–3427 (2016)
Zhang, J., et al.: Automatic craniomaxillofacial landmark digitization via segmentation-guided partially-joint regression forest model and multiscale statistical features. IEEE Trans. Biomed. Eng. 63(9), 1820–1829 (2016)
Shen, D., Davatzikos, C.: An adaptive-focus deformable model using statistical and geometric information. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 906–913 (2000)
Yan, J., et al.: Three-dimensional CT measurement for the craniomaxillofacial structure of normal occlusion adults in Jiangsu, Zhejiang and Shanghai Area. China J. Oral Maxillofac. Surg. 8, 2–9 (2010)
Acknowledgment
This work was supported in part by NIH grants (R01 DE022676 and R01 DE027251).
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Xiao, D. et al. (2019). Estimating Reference Bony Shape Model for Personalized Surgical Reconstruction of Posttraumatic Facial Defects. In: Shen, D., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science(), vol 11768. Springer, Cham. https://doi.org/10.1007/978-3-030-32254-0_37
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DOI: https://doi.org/10.1007/978-3-030-32254-0_37
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