Convolutional neural network-based classification of craniosynostosis and suture lines from multi-view cranial X-rays

Convolutional neural network-based classification of craniosynostosis and suture lines from multi-view cranial X-rays

Abstract Early and precise diagnosis of craniosynostosis (CSO), which involves premature fusion of cranial sutures in infants, is crucial for effective treatment. Although computed topography offers detailed imaging, its high radiation poses risks, especially to children. Therefore, we propose a dee...

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Bibliographic Details
Main Authors: Seung Min Kim, Ji Seung Yang, Jae Woong Han, Hyung Il Koo, Tae Hoon Roh, Soo Han Yoon
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Craniosynostosis
Suture line
Transfer learning
Deep learning
Convolutional neural network
Skull X-ray
Online Access:https://doi.org/10.1038/s41598-024-77550-z
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https://doi.org/10.1038/s41598-024-77550-z

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