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Cranial Sutures

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Convolutional neural network-assisted diagnosis of midpalatal suture maturation stage in cone-beam computed tomography.

Journal of dentistry
OBJECTIVES: The selection of treatment for maxillary expansion is closely related to the calcification degree of the midpalatal suture. A classification method for individual assessment of the morphology of midpalatal suture in cone-beam computed tom...

Age Estimation by Machine Learning and CT-Multiplanar Reformation of Cranial Sutures in Northern Chinese Han Adults.

Fa yi xue za zhi
OBJECTIVES: To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation (MPR), and to explore the applicability of cranial suture closure rule in age estimation of northern ...

Prediction of midpalatal suture maturation stage based on transfer learning and enhanced vision transformer.

BMC medical informatics and decision making
BACKGROUND: Maxillary expansion is an important treatment method for maxillary transverse hypoplasia. Different methods of maxillary expansion should be carried out depending on the midpalatal suture maturation levels, and the diagnosis was validated...

MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce diagnostic-quality images of bone on a timeline suitable for clinical use. We developed automated moti...

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

Scientific reports
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...