Generative-Adversarial-Network-Based Data Augmentation for the Classification of Craniosynostosis

Generative-Adversarial-Network-Based Data Augmentation for the Classification of Craniosynostosis

Craniosynostosis is a congenital disease characterized by the premature closure of one or multiple sutures of the infant’s skull. For diagnosis, 3D photogrammetric scans are a radiation-free alternative to computed tomography. However, data is only sparsely available and the role of data augmentatio...

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Bibliographic Details
Main Authors: Kaiser Christian, Schaufelberger Matthias, Kühle Reinald Peter, Wachter Andreas, Weichel Frederic, Hagen Niclas, Ringwald Friedemann, Eisenmann Urs, Engel Michael, Freudlsperger Christian, Nahm Werner
Format: Article
Language:English
Published: De Gruyter 2022-09-01
Series:Current Directions in Biomedical Engineering
Subjects:
generative adversarial network
classification
craniosynostosis
data augmentation
Online Access:https://doi.org/10.1515/cdbme-2022-1005

Internet

https://doi.org/10.1515/cdbme-2022-1005

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