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Analyzing infant head flatness and asymmetry using kernel density estimation of directional surface data from a craniofacial 3D model
Author(s) -
Vuollo Ville,
Holmström Lasse,
Aarnivala Henri,
Harila Virpi,
Heikkinen Tuomo,
Pirttiniemi Pertti,
Valkama Arja Marita
Publication year - 2016
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7032
Subject(s) - kernel density estimation , asymmetry , flatness (cosmology) , craniofacial , kernel (algebra) , head (geology) , skull , computer science , deformation (meteorology) , support vector machine , artificial intelligence , mathematics , orthodontics , pattern recognition (psychology) , statistics , medicine , geology , anatomy , physics , geomorphology , oceanography , cosmology , quantum mechanics , combinatorics , estimator , psychiatry
Infant skull deformation is analyzed using the distribution of head normal vector directions computed from a 3D image. Severity of flatness and asymmetry are quantified by functionals of the kernel estimate of the normal vector direction density. Using image data from 99 infants and clinical deformation ratings made by experts, our approach is compared with some recently suggested methods. The results show that the proposed method performs competitively. Copyright © 2016 John Wiley & Sons, Ltd.