Assessing craniofacial growth and form without landmarks: a new automatic approach based on spectral methods
Résumé
We present a novel method for the morphometric analysis of series of 3D shapes, and demonstrate its relevance for the detection and quantification of two craniofacial anomalies: trigonocephaly and metopic ridges, using CT-scans of young children. Our approach is fully automatic, and does not rely on manual landmark placement and annotations. Our approach furthermore allows to differentiate shape classes, enabling successful differential diagnosis between trigonocephaly and metopic ridges, two related conditions characterized by triangular foreheads. These results were obtained using recent developments in automatic non-rigid 3D shape correspondence methods and specifically spectral approaches based on the functional map framework. Our method can capture local changes in geometric structure, in contrast to methods based, for instance, on global shape descriptors. As such, our approach allows to perform automatic shape classification and provides visual feedback on shape regions associated with different classes of deformations. The flexibility and generality of our approach paves the way for the application of spectral methods in quantitative medicine.
Mots clés
Morphometrics Spectral analysis Craniofacial malformation Diagnostic tool Landmark-free morphometrics Metopic ridge Skull malformation Trigonocephaly Functional maps
Morphometrics
Spectral analysis
Craniofacial malformation
Diagnostic tool
Landmark-free morphometrics
Metopic ridge
Skull malformation
Trigonocephaly
Functional maps
Domaines
Informatique [cs]Origine | Fichiers produits par l'(les) auteur(s) |
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