Evaluation of automated detection of head position on lateral cephalometric radiographs based on deep learning techniques.
Journal:
Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
PMID:
37302431
Abstract
BACKGROUND: Lateral cephalometric radiograph (LCR) is crucial to diagnosis and treatment planning of maxillofacial diseases, but inappropriate head position, which reduces the accuracy of cephalometric measurements, can be challenging to detect for clinicians. This non-interventional retrospective study aims to develop two deep learning (DL) systems to efficiently, accurately, and instantly detect the head position on LCRs.