AIMC Topic: Craniosynostoses

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Application and Accuracy of Craniomaxillofacial Plastic Surgery Robot in Congenital Craniosynostosis Surgery.

The Journal of craniofacial surgery Mar 20, 2023
OBJECTIVE: The objective of this study was to observe the accuracy and security of the craniomaxillofacial plastic surgery robot in congenital craniosynostosis surgery and to enhance and improve its performance.
Animals Skull Surgery, Plastic Swine, Miniature Swine Robotics Craniosynostoses
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Quantifying the Severity of Metopic Craniosynostosis Using Unsupervised Machine Learning.

Plastic and reconstructive surgery Nov 10, 2022
BACKGROUND: Quantifying the severity of head shape deformity and establishing a threshold for operative intervention remains challenging in patients with metopic craniosynostosis (MCS). This study combines three-dimensional skull shape analysis with ...
Craniosynostoses Skull Infant Unsupervised Machine Learning Humans Reproducibility of Results
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Application of Deep Learning Techniques for Automated Diagnosis of Non-Syndromic Craniosynostosis Using Skull.

The Journal of craniofacial surgery Mar 9, 2022
Non-syndromic craniosynostosis (NSCS) is a disease, in which a single cranial bone suture is prematurely fused. The early intervention of the disease is associated with a favorable outcome at a later age, so appropriate screening of NSCS is essential...
Retrospective Studies Infant Deep Learning Humans Plagiocephaly Craniosynostoses Skull
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Convolutional mesh autoencoders for the 3-dimensional identification of FGFR-related craniosynostosis.

Scientific reports Feb 9, 2022
Clinical diagnosis of craniofacial anomalies requires expert knowledge. Recent studies have shown that artificial intelligence (AI) based facial analysis can match the diagnostic capabilities of expert clinicians in syndrome identification. In genera...
Humans Artificial Intelligence Computer Simulation Face Head Imaging, Three-Dimensional Image Processing, Computer-Assisted Craniosynostoses Tomography, X-Ray Computed Infant
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"Validation of Artificial Intelligence Severity Assessment in Metopic Craniosynostosis".

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association Nov 17, 2021
OBJECTIVE: Several severity metrics have been developed for metopic craniosynostosis, including a recent machine learning-derived algorithm. This study assessed the diagnostic concordance between machine learning and previously published severity ind...
Tomography, X-Ray Computed Infant Craniosynostoses Humans Artificial Intelligence Retrospective Studies
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Image processing and machine learning for telehealth craniosynostosis screening in newborns.

Journal of neurosurgery. Pediatrics Mar 19, 2021
OBJECTIVE: The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was ...
Telemedicine Image Interpretation, Computer-Assisted Female Humans Infant, Newborn Machine Learning Male Software Mass Screening Craniosynostoses Cephalometry
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Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis.

Scientific reports Sep 18, 2020
Craniosynostosis is a condition in which cranial sutures fuse prematurely, causing problems in normal brain and skull growth in infants. To limit the extent of cosmetic and functional problems, swift diagnosis is needed. The goal of this study is to ...
Infant Case-Control Studies Deep Learning Humans Photogrammetry Head Imaging, Three-Dimensional Craniosynostoses Facial Bones
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Computer Simulation and Optimization of Cranial Vault Distraction.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association Dec 14, 2017
OBJECTIVE: The objective of this study was to validate the proof of concept of a computer-simulated cranial distraction, demonstrating accurate shape and end volume.
Surgery, Computer-Assisted Proof of Concept Study Skull Craniosynostoses Osteogenesis, Distraction Male Infant Child, Preschool Imaging, Three-Dimensional Treatment Outcome Tomography, X-Ray Computed Female Infant, Newborn Humans Computer Simulation
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Bone Fusion in Normal and Pathological Development is Constrained by the Network Architecture of the Human Skull.

Scientific reports Jun 13, 2017
Craniosynostosis, the premature fusion of cranial bones, affects the correct development of the skull producing morphological malformations in newborns. To assess the susceptibility of each craniofacial articulation to close prematurely, we used a ne...
Skull Bone Development Spinal Fusion Bone and Bones Infant, Newborn Craniosynostoses Bayes Theorem Humans Neural Networks, Computer Algorithms
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CNN-Based Classification of Craniosynostosis Using 2D Distance Maps.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Craniosynostosis is a condition associated with the premature fusion of skull sutures affecting infants. 3D photogrammetric scans are a promising alternative to computed tomography scans in cases of single suture or nonsyndromic synostosis for diagno...
Tomography, X-Ray Computed Infant Craniosynostoses Bone and Bones Humans Neural Networks, Computer
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