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...
BACKGROUND: Skull radiography, an assessment method for initial diagnosis and post-operative follow-up, requires substantial retaking of various types of radiographs. During retaking, a radiologic technologist estimates a patient's rotation angle fro...
PURPOSE: Accurate positioning is essential for radiography, and it is especially important to maintain image reproducibility in follow-up observations. The decision on re-taking radiographs is entrusting to the individual radiological technologist. T...
OBJECTIVE: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children.
We present a 3D deep learning framework that can generate a complete cranial model using a defective one. The Boolean subtraction between these two models generates the geometry of the implant required for surgical reconstruction. There is little or ...
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...
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...
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...
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...
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...