Volumetric reconstruction of craniofacial structures from 2D lateral cephalograms by regression forest

The 3D reconstruction is an essential step to measure the craniofacial morphological changes from the historical growth database with only 2D cephalograms. In this paper, we propose a novel regression-forest-based method to estimate the volumetric intensity images from a lateral cephalogram. The regression forest can produce a prediction of the volumetric craniofacial structure as a mixture of Gaussian by weighted aggregating the distributions from trees. The dense anatomical structure can be reconstructed with no time-consuming digitally-reconstructed-radiographs (DRR) in the online testing process. The experiments demonstrate the proposed method can reconstruct volumetric intensity images from the lateral cephalograms effectively.