High energy traumatic impact of the craniofacial skeleton is an inevitable consequence of today's fast paced society. The work presented in this paper leverages recent advances in computer vision, computer visualization and computeraided manufacturing/design to reduce the fractures and reconstruct the craniofacial skeleton in silico. First, two popular surface matching algorithms namely the Iterative Closest Point (ICP) algorithm and the Data Aligned Rigidity Constrained Exhaustive Search (DARCES) algorithm are applied individually to the problem of craniofacial reconstruction. The potential benefits and shortcomings of both these algorithms are explored. A synergetic combination of the DARCES and ICP algorithms where the output of the DARCES algorithm is fed as input to the ICP algorithm is shown to result in improved performance in terms of both, reconstruction accuracy and execution time.
Suchendra M. Bhandarkar, Ananda S. Chowdhury, Yaro