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) …

BACKGROUND: The authors have developed pretrained machine learning (ML) models to
evaluate neonatal head shape deformities using top-down and facial orthogonal …

Positional cranial deformities are relatively common conditions, characterized by asymmetry
and changes in skull shape. Although three-dimensional (3D) scanning is the gold standard …

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 …

Purpose Skull radiography (SR) and Computed Tomography (CT) are still proposed as the
first-line imaging choice for the diagnosis of craniosynostosis (CS) in children with abnormal …

Background: Evaluation of surgical treatment for craniosynostosis is typically based on
subjective visual assessment or simple clinical metrics of cranial shape that are prone to …

Objective: Diagnosis of craniosynostosis using photogrammetric 3D surface scans is a
promising radiation-free alternative to traditional computed tomography. We propose a 3D …

Background: Craniosynostosis is a condition caused by the premature fusion of skull
sutures, leading to irregular growth patterns of the head. Three-dimensional …

We present a technique for the computational analysis of craniosynostosis from CT images.
Our fully automatic methodology uses a statistical shape model to produce diagnostic …

BACKGROUND: Radiography, typically the first-line imaging study for diagnosis of
craniosynostosis, exposes infants to ionizing radiation. We aimed to compare the accuracy …