TY - GEN
T1 - A novel multifaceted virtual craniofacial surgery scheme using computer vision
AU - Chowdhury, A. S.
AU - Bhandarkar, S. M.
AU - Tollner, E. W.
AU - Zhang, G.
AU - Yu, J. C.
AU - Ritter, E.
PY - 2005
Y1 - 2005
N2 - The paper addresses the problem of virtual craniofacial reconstruction from a set of Computer Tomography (CT) images, with the multiple objectives of achieving accurate local matching of the opposable fracture surfaces and preservation of the global shape symmetry and the biomechanical stability of the reconstructed mandible. The first phase of the reconstruction, with the mean squared error as the performance metric, achieves the best possible local surface matching using the Iterative Closest Point (ICP) algorithm and the Data Aligned Rigidity Constrained Exhaustive Search (DARCES) algorithm each used individually and then in a synergistic combination. The second phase, which consists of an angular perturbation scheme, optimizes a composite reconstruction metric. The composite reconstruction metric is a linear combination of the mean squared error, a global shape symmetry term and the surface area which is shown to be a measure of biomechanical stability. Experimental results, including a thorough validation scheme on simulated fractures in phantoms of the craniofacial skeleton, are presented.
AB - The paper addresses the problem of virtual craniofacial reconstruction from a set of Computer Tomography (CT) images, with the multiple objectives of achieving accurate local matching of the opposable fracture surfaces and preservation of the global shape symmetry and the biomechanical stability of the reconstructed mandible. The first phase of the reconstruction, with the mean squared error as the performance metric, achieves the best possible local surface matching using the Iterative Closest Point (ICP) algorithm and the Data Aligned Rigidity Constrained Exhaustive Search (DARCES) algorithm each used individually and then in a synergistic combination. The second phase, which consists of an angular perturbation scheme, optimizes a composite reconstruction metric. The composite reconstruction metric is a linear combination of the mean squared error, a global shape symmetry term and the surface area which is shown to be a measure of biomechanical stability. Experimental results, including a thorough validation scheme on simulated fractures in phantoms of the craniofacial skeleton, are presented.
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U2 - 10.1007/11569541_16
DO - 10.1007/11569541_16
M3 - Conference contribution
AN - SCOPUS:33646687707
SN - 3540294112
SN - 9783540294115
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 146
EP - 159
BT - Computer Vision for Biomedical Image Applications - First International Workshop, CVBIA 2005, Proceedings
T2 - 1st International Workshop on Computer Vision for Biomedical Image Applications, CVBIA 2005
Y2 - 21 October 2005 through 21 October 2005
ER -