Chowdhury A.S., Bhandarkar S.M. Computer Vision-Guided Virtual Craniofacial Surgery: A Graph-Theoretic and Statistical Perspective

Springer, 2011. — 190 p. — (Advances in Computer Vision and Pattern Recognition). — ISBN: 0857292951.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.Overview and FoundationsGraph-Theoretic Foundations
A Statistical Primer
Virtual Craniofacial Reconstruction
Virtual Single-fracture Mandibular Reconstruction
Virtual Multiple-fracture Mandibular Reconstruction
Computer-aided Fracture Detection
Fracture Detection using Bayesian Inference
Fracture Detection in an MRF-based Hierarchical Bayesian Framework
Fracture Detection using Max-Flow Min-Cut
Concluding Remarks
GUI Design and Research Synopsis