Symbolic shape descriptors for classifying craniosynostosis deformations from skull imaging.
Craniosynostosis is a serious condition of childhood, caused by the early fusion of the sutures of the skull. The resulting abnormal skull development can lead to severe deformities, increased intra-cranial pressure, as well as vision, hearing and breathing problems. In this work we develop a novel approach to accurately classify deformations caused by metopic and isolated sagittal synostosis. Our method combines a novel set of symbolic shape descriptors and off-the-shelf classification tools to model morphological variations that characterize the synostotic skull. We demonstrate the efficacy of our methodology in a series of large-scale classification experiments that contrast the performance of our proposed symbolic descriptors to those of traditional numeric descriptors, such as clinical severity indices, Fourier-based descriptors and cranial image quantifications.
Lin
H
H
Department of Biomedical and Health Informatics, University of Washington.
Ruiz-Correa
S
S
Shapiro
L G
LG
Hing
A
A
Cunningham
M L
ML
Speltz
M
M
Sze
R
R