• Ananda S. ChowdhuryEmail author
  • Suchendra M. Bhandarkar
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)


This monograph is devoted to an in-depth exposition of the various issues that arise in virtual reconstructive craniofacial surgery and is written from a graph-theoretic and statistical perspective. We discuss some sophisticated techniques from computer vision, graph theory, and statistics and demonstrate how they can be employed to address the various challenging problems that arise in virtual reconstructive craniofacial surgery. The solutions presented here are quite general in their scope and applicability. Consequently, they can be easily applied to tackle similar problems that arise in related areas such as reconstructive orthopedic surgery and seemingly unrelated areas such as archeology, where ancient artifacts such as pottery need to be virtually reconstructed from unearthed broken pieces. This will be more evident in the discussion of the individual problems in the later chapters of the monograph. In this chapter, we first describe the anatomy of craniofacial fractures. Next, we discuss the state-of-the-art in the field of virtual reconstructive craniofacial surgery and highlight the importance of our contributions. We end this chapter by outlining the organization of this monograph.


Iterative Close Point Iterative Close Point Mandibular Fracture Craniofacial Surgery Craniofacial Skeleton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Ananda S. Chowdhury
    • 1
    Email author
  • Suchendra M. Bhandarkar
    • 2
  1. 1.Department of Electronics & Telecommunication EngineeringJadavpur UniversityKolkataIndia
  2. 2.Department of Computer ScienceThe University of GeorgiaAthensUSA

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