Estimation based on vectorized surfaces for craniofacial reconstruction
Françoise M. Tilotta, Joan Glaunès, Frédéric Richard, Yves Rozenholc (University Paris Descartes)

In recent years, the development of medical imaging has had a major impact on facial reconstruction. New strategies have been proposed to reconstitute the morphology of a face from the observation of a skull. Our image processing includes 1/ the segmentation of both skull and external skin surface for each slice; 2/ the construction of two 3D surfaces by meshing curves on successive slices. Then 39 landmarks are manually located on each skull mesh. These steps allow to compute geodesics on the meshed surface and extract anatomically identified feature from the bone surface (bone patch). Using registration techniques via RKHS for surfaces it is possible to construct a "distance" between individual features on the skull (bone patch) and to compute average of the corresponding skin features in a statistical learning framework. In our work, we choose a local and individual approach based on the used of dense meshes associated to a large collection of landmarks directly extracted from CT-scans. Based on a database containning 85 CT-Scan of the whole head performed on volunteers European, our method allows to reconstruct local features on the skull like the nose with a good accuracy.

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