Computer Vision-Guided Virtual Craniofacial Surgery
A Graph-Theoretic and Statistical Perspective
Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Health & Well Being, Medical, Medical Science, Biochemistry, General Computing
| Author: | Ananda S. Chowdhury, Suchendra M. Bhandarkar | ISBN: | 9780857292964 |
| Publisher: | Springer London | Publication: | March 19, 2011 |
| Imprint: | Springer | Language: | English |
| Author: | Ananda S. Chowdhury, Suchendra M. Bhandarkar |
| ISBN: | 9780857292964 |
| Publisher: | Springer London |
| Publication: | March 19, 2011 |
| Imprint: | Springer |
| Language: | English |
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.
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.
