Chowdhury / Bhandarkar Computer Vision-Guided Virtual Craniofacial Surgery

A Graph-Theoretic and Statistical Perspective
1. Auflage 2011
ISBN: 978-0-85729-296-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 166 Seiten

Reihe: Advances in Computer Vision and Pattern Recognition

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.

Autoren/Hrsg.

Chowdhury, Ananda S.

Bhandarkar, Suchendra M.

Inhaltsverzeichnis

1;Foreword;6
2;Preface;8
3;Contents;12
4;List of Figures;15
5;List of Tables;20
6;Part I: Overview and Foundations;21
6.1;Chapter 1: Introduction;22
6.1.1;1.1 Craniofacial Fractures;22
6.1.2;1.2 State-of-the-Art Virtual Craniofacial Surgery;27
6.1.3;1.3 The Importance of Computer-Assisted Surgical Planning;28
6.1.4;1.4 Organization of the Monograph;31
6.2;Chapter 2: Graph-Theoretic Foundations;33
6.2.1;2.1 Some Basic Terminology;33
6.2.2;2.2 Matchings in Graphs;35
6.2.3;2.3 Isomorphism and Automorphism of Graphs;37
6.2.4;2.4 Network Flows;38
6.3;Chapter 3: A Statistical Primer;42
6.3.1;3.1 Probability;42
6.3.2;3.2 Statistical Inference;45
6.3.3;3.3 Bayesian Statistics;47
6.3.4;3.4 Random Fields, Bayesian Restoration, and Stochastic Relaxation;49
7;Part II: Virtual Craniofacial Reconstruction;52
7.1;Chapter 4: Virtual Single-Fracture Mandibular Reconstruction;53
7.1.1;4.1 Motivation;53
7.1.2;4.2 Chapter Organization;53
7.1.3;4.3 Related Work and Our Contribution;54
7.1.4;4.4 Image Processing;55
7.1.4.1;4.4.1 Thresholding;57
7.1.4.2;4.4.2 Connected Component Labeling;58
7.1.4.3;4.4.3 Contour Data Extraction;58
7.1.5;4.5 Surface Matching Using Type-0 Constraints;59
7.1.5.1;4.5.1 Surface Registration Using the ICP Algorithm;59
7.1.5.2;4.5.2 Registration Using the DARCES Algorithm;61
7.1.5.3;4.5.3 Registration Using the Hybrid DARCES-ICP Algorithm;62
7.1.6;4.6 Improved Surface Matching with Surface Irregularity Modeling;63
7.1.6.1;4.6.1 Curvature-Based Surface Irregularity Estimation;63
7.1.6.2;4.6.2 Fuzzy Set Theory-Based Surface Irregularity Extraction;65
7.1.6.3;4.6.3 Reward/Penalty Schemes;66
7.1.7;4.7 Improved Surface Matching with Type-1 Constraints;67
7.1.7.1;4.7.1 Cycle Graph Automorphs as Initial ICP States;68
7.1.7.2;4.7.2 Selection of the Best Initial State;68
7.1.7.3;4.7.3 Registration Using the Hybrid Geometric-ICP Algorithm;70
7.1.8;4.8 Bilateral Symmetry of the Human Mandible;71
7.1.9;4.9 Biomechanical Stability of the Human Mandible;72
7.1.10;4.10 Composite Reconstruction Using MSE, Symmetry, and Stability;74
7.1.11;4.11 Experimental Results;76
7.1.12;4.12 Conclusion and Future Work;81
7.2;Chapter 5: Virtual Multiple-Fracture Mandibular Reconstruction;87
7.2.1;5.1 Motivation;87
7.2.2;5.2 Chapter Organization;88
7.2.3;5.3 Related Work and Our Contribution;88
7.2.4;5.4 Image Processing;91
7.2.5;5.5 Design of a Score Matrix;92
7.2.5.1;5.5.1 Modeling Spatial Proximity;94
7.2.5.2;5.5.2 Modeling Surface Characteristics;94
7.2.5.3;5.5.3 Score Matrix Elements;95
7.2.6;5.6 Identification of Opposable Fracture Surfaces;96
7.2.6.1;5.6.1 Combinatorial Nature of the Reconstruction Problem;96
7.2.6.2;5.6.2 Maximum Weight Graph Matching for Restricting the Reconstruction Options;97
7.2.7;5.7 Pairwise Registration of the Fracture Surfaces;98
7.2.8;5.8 Shape Monitoring of the Reconstructed Mandible;98
7.2.9;5.9 Experimental Results;100
7.2.10;5.10 Conclusion and Future Work;103
8;Part III: Computer-Aided Fracture Detection;104
8.1;Chapter 6: Fracture Detection Using Bayesian Inference;105
8.1.1;6.1 Motivation;105
8.1.2;6.2 Chapter Organization;106
8.1.3;6.3 Related Work and Our Contribution;106
8.1.4;6.4 Image Processing;108
8.1.5;6.5 Fracture Point Detection in 2D CT Image Slices;109
8.1.5.1;6.5.1 Initial Pool of Fracture Points;110
8.1.5.2;6.5.2 Final Pool of Fracture Points;110
8.1.6;6.6 Stable Fracture Points in a CT Image Sequence;111
8.1.6.1;6.6.1 The Kalman Filter as a Bayesian Inference Process;111
8.1.6.2;6.6.2 Concept of Spatial Consistency;112
8.1.7;6.7 Experimental Results;115
8.1.8;6.8 Conclusion and Future Work;121
8.2;Chapter 7: Fracture Detection in an MRF-Based Hierarchical Bayesian Framework;124
8.2.1;7.1 Motivation;124
8.2.2;7.2 Chapter Organization;125
8.2.3;7.3 Related Work and Our Contribution;126
8.2.4;7.4 Coarse Fracture Localization;127
8.2.4.1;7.4.1 Localization of the Mandible;128
8.2.4.2;7.4.2 Determination of the Fracture-Containing Symmetric Block Pair(s);129
8.2.4.3;7.4.3 Identification of the Fracture-Containing Image Half;130
8.2.5;7.5 Hierarchical Bayesian Restoration Framework;130
8.2.5.1;7.5.1 Statistical Model;131
8.2.5.2;7.5.2 Modeling of the Stochastic Degradation Matrix;133
8.2.6;7.6 Experimental Results;135
8.2.7;7.7 Conclusion and Future Work;147
8.3;Chapter 8: Fracture Detection Using Max-Flow Min-Cut;150
8.3.1;8.1 Motivation;150
8.3.2;8.2 Chapter Organization;150
8.3.3;8.3 Related Work and Our Contribution;151
8.3.4;8.4 Max-Flow Min-Cut in a 2D Flow Network;152
8.3.4.1;8.4.1 Construction of the 2D Flow Network;152
8.3.4.2;8.4.2 Correctness of the 2D Flow Network Model;154
8.3.5;8.5 Max-Flow Min-Cut in 3D;154
8.3.5.1;8.5.1 Construction of the 3D Flow Network;154
8.3.5.2;8.5.2 Correctness of the 3D Flow Network Model;156
8.3.6;8.6 Experimental Results;156
8.3.7;8.7 Conclusion and Future Work;159
9;Part IV: Concluding Remarks;161
9.1;Chapter 9: GUI Design and Research Synopsis;162
9.1.1;9.1 Chapter Organization;162
9.1.2;9.2 Design of the Graphical User Interface;162
9.1.3;9.3 Synopsis;165
9.1.4;9.4 Virtual Reconstructive Surgery-An Interdisciplinary Research Perspective;166
9.1.5;9.5 Future Research Directions;167
10;References;169
11;Index;176