Computer Vision-Guided Virtual Craniofacial Surgery - A Graph-Theoretic and Statistical Perspective (Paperback, 2011 ed.)

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.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Series:	Advances in Computer Vision and Pattern Recognition
Release date:	April 2013
First published:	2011
Authors:	Ananda S. Chowdhury • Suchendra M. Bhandarkar
Dimensions:	235 x 155 x 10mm (L x W x T)
Format:	Paperback
Pages:	166
Edition:	2011 ed.
ISBN-13:	978-1-4471-2645-4
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Medicine > Other branches of medicine > Medical imaging > Radiology Promotions
LSN:	1-4471-2645-9
Barcode:	9781447126454

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