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This unique text/reference discusses in depth the two integral components of reconstructive surgery; fracture detection, and reconstruction from broken bone fragments. In addition to supporting its application-oriented viewpoint with detailed coverage of theoretical issues, the work incorporates useful algorithms and relevant concepts from both graph theory and statistics. Topics and features: presents practical solutions for virtual craniofacial reconstruction and computer-aided fracture detection; discusses issues of image registration, object reconstruction, combinatorial pattern matching, and detection of salient points and regions in an image; investigates the concepts of maximum-weight graph matching, maximum-cardinality minimum-weight matching for a bipartite graph, determination of minimum cut in a flow network, and construction of automorphs of a cycle graph; examines the techniques of Markov random fields, hierarchical Bayesian restoration, Gibbs sampling, and Bayesian inference.
Autor: Bhandarkar, Suchendra M. Chowdhury, Ananda S.
ISBN: 9780857292957
Sprache: Englisch
Seitenzahl: 166
Produktart: Gebunden
Verlag: Springer London
Veröffentlicht: 28.03.2011
Untertitel: A Graph-Theoretic and Statistical Perspective
Schlagworte: Bayesian Inference Computed Tomography Fracture Detection Graph Automorphism Graph Matching Markov Random Field Max-Flow Min-Cut Virtual Reconstruction

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