Computer Vision-Guided Virtual Craniofacial Surgery A Graph-Theoretic and Statistical Perspective Advances in Computer Vision and Pattern Recognition

By:

Ananda S. Chowdhury

Contributor(s):

Suchendra M. Bhandarkar

Material type: Text

TextPublication details: Publisher Springer Science & Business Media 2011Edition: illustratedDescription: 166 pagesISBN:

085729296X
9780857292964

Subject(s):

DDC classification:

617 CHO

Contents:

Contents: Overview and Foundations Virtual Craniofacial Reconstruction ComputerAided Fracture Detection Concluding Remarks References Index

Summary: Recent advances in both scanning instruments and supporting software have transitioned their impact from merely outside the operating room to inside the surgical theater, making intra-operative 3D imaging a reality. This unique text/reference examines the important application of computer vision and pattern recognition to medical science, with a specific focus on reconstructive craniofacial surgery. The book 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, which can also be applied to related fields such as radiology, orthopedic surgery and histopathology; 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; includes a Foreword by Dr. Jack C. Yu, Milford B. Hatcher Professor of Surgery at the Medical College of Georgia, Augusta, GA, USA. This practical text will be of great resource value to researchers and graduate students from a broad spectrum of disciplines including computer science, electrical engineering, biomedical engineering and statistics. Clinical practitioners such as plastic surgeons, orthopedic surgeons and radiologists will also find much of interest in the book.p>/body

Item type: E-BOOKS

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Holdings
Item type	Current library	Collection	Call number	Status	Barcode
E-BOOKS	MWALIMU NYERERE LEARNING RESOURCES CENTRE-CUHAS BUGANDO	NFIC	617 CHO (Browse shelf(Opens below))	-1	EBS12233

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Previous	617 BOR Oxford Assess and Progress Clinical Surgery	617 BOY Aaos Comprehensive Orthopaedic Review /	617 CAP Atlas of Endoscopic Anatomy for Endonasal Intracranial Surgery	617 CHO Computer Vision-Guided Virtual Craniofacial Surgery A Graph-Theoretic and Statistical Perspective	617 COR Introduction to Spine Surgery Essentials for ORP, Fellows, and Residents	617 COV General surgery risk reduction /	617 DAN Acute Care General Surgery Workup and Management	Next

Contents:

Overview and Foundations

Virtual Craniofacial Reconstruction

ComputerAided Fracture Detection

Concluding Remarks

References

Index

Recent advances in both scanning instruments and supporting software have transitioned their impact from merely outside the operating room to inside the surgical theater, making intra-operative 3D imaging a reality.

This unique text/reference examines the important application of computer vision and pattern recognition to medical science, with a specific focus on reconstructive craniofacial surgery. The book 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, which can also be applied to related fields such as radiology, orthopedic surgery and histopathology; 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; includes a Foreword by Dr. Jack C. Yu, Milford B. Hatcher Professor of Surgery at the Medical College of Georgia, Augusta, GA, USA.

This practical text will be of great resource value to researchers and graduate students from a broad spectrum of disciplines including computer science, electrical engineering, biomedical engineering and statistics. Clinical practitioners such as plastic surgeons, orthopedic surgeons and radiologists will also find much of interest in the book.p>/body

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