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{ "item_title" : "Computer Vision-Guided Virtual Craniofacial Surgery", "item_author" : [" Ananda S. Chowdhury", "Suchendra M. Bhandarkar "], "item_description" : "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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/44/712/645/1447126459_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Computer Vision-Guided Virtual Craniofacial Surgery|Ananda S. Chowdhury

Computer Vision-Guided Virtual Craniofacial Surgery : A Graph-Theoretic and Statistical Perspective

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Overview

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.

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Details

  • ISBN-13: 9781447126454
  • ISBN-10: 1447126459
  • Publisher: Springer
  • Publish Date: April 2013
  • Dimensions: 9.21 x 6.14 x 0.41 inches
  • Shipping Weight: 0.61 pounds
  • Page Count: 166

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