AIMC Topic: Skull

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

The Journal of craniofacial surgery
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.

Facial reconstruction using 3-D computerized method: A scoping review of Methods, current Status, and future developments.

Legal medicine (Tokyo, Japan)
Facial reconstruction (otherwise known as facial approximation) is an alternative method that has been widely accepted in forensic anthropological and archaeological circumstances. This method is considered useful for creating the virtual face of a p...

Assessment of Thermal Damage from Robot-Drilled Craniotomy for Cranial Window Surgery in Mice.

Journal of visualized experiments : JoVE
Cranial window surgery allows for the imaging of brain tissue in live mice with the use of multiphoton or other intravital imaging techniques. However, when performing any craniotomy by hand, there is often thermal damage to brain tissue, which is in...

Quantifying the Severity of Metopic Craniosynostosis Using Unsupervised Machine Learning.

Plastic and reconstructive surgery
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 ...

Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR.

PloS one
The segmentation of medical and dental images is a fundamental step in automated clinical decision support systems. It supports the entire clinical workflow from diagnosis, therapy planning, intervention, and follow-up. In this paper, we propose a no...

Deep learning-based framework for automatic cranial defect reconstruction and implant modeling.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This article presents a robust, fast, and fully automatic method for personalized cranial defect reconstruction and implant modeling.

Deep-learning synthesized pseudo-CT for MR high-resolution pediatric cranial bone imaging (MR-HiPCB).

Magnetic resonance in medicine
PURPOSE: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop a deep learning method to synthesize pseudo-CT (pCT) images for MR high-resolution pediatric cranial...

Machine learning and geometric morphometrics to predict obstructive sleep apnea from 3D craniofacial scans.

Sleep medicine
BACKGROUND: Obstructive sleep apnea (OSA) remains massively underdiagnosed, due to limited access to polysomnography (PSG), the highly complex gold standard for diagnosis. Performance scores in predicting OSA are evaluated for machine learning (ML) a...

Automatic measurement of fetal head circumference using a novel GCN-assisted deep convolutional network.

Computers in biology and medicine
The growth of the fetus can be effectively monitored by measuring the fetal head circumference (HC) in ultrasound images. Moreover, it is the key to assessing the fetus's health. Ultrasound fetal head image boundary is blurred. The ultrasound sound s...

A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium.

Scientific reports
The aim of this study is to test whether sex prediction can be made by using machine learning algorithms (ML) with parameters taken from computerized tomography (CT) images of cranium and mandible skeleton which are known to be dimorphic. CT images o...