Abstract
In this chapter, we discuss in detail the various aspects of the problem of virtual mandibular reconstruction in the presence of a single fracture. Much of this discussion is applicable not only to situations that involve exclusively a single fracture, but also to multiple fracture scenarios wherein the fractures are fixated one at a time in the operating room. Thus, the problem of mandibular reconstruction in the case of a single fracture assumes paramount importance in most craniofacial trauma cases. We discuss various surface matching techniques such as the Iterative Closest Point (ICP) algorithm, the Data Aligned Rigidity Constrained Exhaustive Search (DARCES) algorithm and improvised variants of the ICP and DARCES algorithms. We also show how incorporating the knowledge of anatomical symmetry and biomechanical stability of a human mandible in the reconstruction process improves the overall reconstruction accuracy. The Maximum Cardinality Minimum Weight Bipartite Graph Matching algorithm, relevant concepts from Graph Automorphism, Fuzzy set-theoretic modeling, and extraction of the mean and Gaussian curvature values from the fracture surfaces are employed at various stages of the reconstruction process and are shown to improve the reconstruction accuracy.
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Chowdhury, A.S., Bhandarkar, S.M. (2011). Virtual Single-Fracture Mandibular Reconstruction. In: Computer Vision-Guided Virtual Craniofacial Surgery. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-296-4_4
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DOI: https://doi.org/10.1007/978-0-85729-296-4_4
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