Computer Vision-Guided Virtual Craniofacial Surgery
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. |
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| ISBN: | 9781447126454 |
| Sprache: | Englisch |
| Seitenzahl: | 166 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer London |
| Veröffentlicht: | 21.04.2013 |
| 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 |