Surface-bounded growth modeling applied to human mandibles.

by Per R. Andresen

IMM Ph.D. Thesis 65, 2000

For a copy of this paper, either Abstract:

This thesis presents mathematical and computational techniques for three dimensional growth modeling applied to human mandibles. The longitudinal shape changes make the mandible a complex bone. The teeth erupt and the condylar processes change direction, from pointing predominantly backward to pointing more upward. The full dataset consists of 31 mandibles from six patients. Each patient is longitudinally CT scanned between three and seven times. Age range is 1 month to 12 years old for the scans.

Growth modeling consists of three overall steps:

  1. extraction of features.
  2. registration of the common features.
  3. model the process that moves the matched points (growth modeling).

A local shape feature called crest line has shown itself to be structurally stable on mandibles. Registration of crest lines (from different mandibles) results in a sparse deformation field, which must be interpolated to yield a spatially dense field. Different methods for constructing the sparse field are compared. Adaptive Gaussian smoothing is the preferred method since it is parameter free and yields good results in practice.

A new method, geometry-constrained diffusion, is used to simplify The most successful growth model is linear and based on results from shape analysis and principal component analysis. The growth model is tested in a cross validation study with good results. The worst case mean modeling error in the cross validation study is 3.7 mm. It occurs when modeling the shape and size of a 12 years old mandible based on the 3 month old scan. When using successively more recent scans as basis for the model the error drops to 2.0 mm for the 11 years old scan. Thus, it seems reasonable to assume that the mandibular growth is linear.

Keywords:
adaptive Gaussian smoothing, aperture-problem, automatic landmark detection, crest lines, CT scans, extremal mesh, geometry-constrained diffusion, homologous points, linear growth modeling, mandible, morphometrics, non-rigid shape-preserving registration, principal component analysis, semi-landmarks, shape analysis, simplest deformation field.

Abstract in Danish:

Denne afhandling anvender matematiske og datamatiske teknikker til tre-dimensional vækst-modellering af underkæber fra mennesker. Den tidsmæssige formændring af kæben, gør den til en kompleks knogle. Tænderne bryder frem og processus condylaris ændrer retning fra at pege overvejende bagud til at pege mere opad. Det fulde datasæt består af 31 underkæber fra seks patienter. Hver patient er CT-skannet over tid mellem tre og syv gange. Kæberne er mellem 1 måned og 12 år gamle.

Vækstmodellering består af 3 overordnede skridt:

  1. bestemmelse af features;
  2. registrering af fælles features
  3. modellering af processen, der flytter de sammenhørende features (vækstmodellering).
En lokal form feature, som kaldes crest line, har vist sig at være strukturel stabil på kæberne. Registrering af crest lines (fra forskellige kæber) resulterer i et sparsomt deformationsfelt, som skal interpoleres for at skabe et kompakt felt. Forskellige metoder til at konstruere et kompakt felt er sammenlignet. Adaptiv gaussisk glatning er den foretrukne, da den er parameterfri og giver gode resultater i praksis.

En ny metode, geometry-constrained diffusion, benyttes til at simplificere deformationsfeltet. Det vises, at vækstmodellen herved forbedres signifikant.

Den mest succesfulde vækstmodel er lineær og baseret på resultater fra formanalyse og principal komponent analyse. Vækstmodellen er blevet testet med gode resultater i et krydsvaliderings-forsøg. Worst case middel-modelleringsfejlen i krydsvalideringsforsøget er 3,7 mm. Fejlen optræder, når formen og størrelsen af en 12 årig underkæbe modelleres, baseret på en skanning fra 3 måneders alderen. Ved successivt at anvendte skanninger af nyere dato som basis for modellen, falder fejlen til 2,0 mm for 11-års skanningen. Det synes derfor rimeligt at antage, at underkæben vokser lineært.


Last update 13-4-2000 by fkc
IMM HomePage