Surface-bounded growth modeling applied to human mandibles
- 1 January 2000
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Medical Imaging
- Vol. 19 (11) , 1053-1063
- https://doi.org/10.1109/42.896780
Abstract
From a set of longitudinal three-dimensional scans of the same anatomical structure, we have accurately modeled the temporal shape and size changes using a linear shape model. On a total of 31 computed tomography scans of the mandible from six patients, 14,851 semilandmarks are found automatically using shape features and a new algorithm called geometry-constrained diffusion. The semilandmarks are mapped into Procrustes space. Principal component analysis extracts a one-dimensional subspace, which is used to construct a linear growth model. The worst case mean modeling error in a cross validation study is 3.7 mm.Keywords
This publication has 27 references indexed in Scilit:
- Feature displacement interpolationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A mixture model for representing shape variationImage and Vision Computing, 1999
- Image registration based on thin-plate splines and local estimates of anisotropic landmark localization uncertaintiesPublished by Springer Nature ,1998
- Building a complete surface model from sparse data using statistical shape models: Application to computer assisted knee surgeryPublished by Springer Nature ,1998
- Matching 3-D anatomical surfaces with non-rigid deformations using octree-splinesInternational Journal of Computer Vision, 1996
- Iterative point matching for registration of free-form curves and surfacesInternational Journal of Computer Vision, 1994
- Multiresolution elastic matchingComputer Vision, Graphics, and Image Processing, 1989
- The structure of imagesBiological Cybernetics, 1984
- Normal and abnormal growth of the mandible. A synthesis of longitudinal cephalometric implant studies over a period of 25 yearsEuropean Journal of Orthodontics, 1983
- On a Theorem Stated by Eckart and YoungPsychometrika, 1963