AN OPEN-SOURCE, THREE-DIMENSIONAL GROWTH MODEL OF THE MANDIBLE

This repository contains all geometrical data and metadata belonging to the paper AN OPEN-SOURCE, THREE-DIMENSIONAL GROWTH MODEL OF THE MANDIBLE by the MAGIC Amsterdam research consortium. The following contents are uploaded:
shapeVectors_original.csv | shape vectors of the original datashapeVectors_rescaled.csv | shape vectors of the rescaled data678 x 62589 matrices where the rows are samples and the columns are shape vectors. The shape vectors are formatted [x1, x2, x3, ..., y1, y2, y3, ..., z1, z2, z3, ...].
PCA_coeff_original.csv | principal component coefficients of the original dataPCA_coeff_rescaled.csv | principal component coefficients of the rescaled data62589 x 677 matrices where each row of these matrices is a variable (x-, y-, or z-coordinate of a vertex) and each column is a principal component.
PCA_score_original.csv | principal component scores of the original dataPCA_score_rescaled.csv | principal component scores of the rescaled data678 x 677 matrices where rows correspond to samples and columns correspond to principal components.
PCA_latent_original.csv | principal component variances of the original dataPCA_latent_rescaled.csv | principal component variances of the rescaled data677 x 1 vectors where each element is an eigenvalue of a principal component.
PCA_mu_original.csv | mean of the original dataPCA_mu_rescaled.csv | mean of the rescaled data1 x 62589 vectors that represent the average shape vector. All (centered) data can be reconstructed as follows: shapeVectors = PCA_score * PCA_coeff' + PCA_mu.
PCA_standardDeviations_original.csv | standard deviations of each sample for each principal component of the original data.PCA_standardDeviations_rescaled.csv | standard deviations of each sample for each principal component of the rescaled data.677 x 678 matrices where the rows are principal components and the columns are samples. The standard deviations were calculated as follows: PCA_standardDeviations = PCA_score' ./ sqrt(PCA_latent).
metadata.csv | This matrix contains the age in years (first column) and biological sex (second column, 1 = male and 2 = female) for all samples (rows).
connectivityList.csv | This matrix defines the mesh of the 3D model of the mandible. The vector in each row represents which vertices define a triangle. Indexing starts at 0, so for use in e.g. Matlab, add 1 to all elements.