Artificial Intelligence for radiographic image analysis

Automated identification of landmarks on lateral cephalogram and cone-beam computed tomography (CBCT) scans can save time for the clinicians and act as a second set of eyes for analysis of radiographic images in diagnosis and treatment planning. Several machine-learning techniques have been utilized for this purpose with varying accuracies. However, high degree of variability in the clinical presentation of orthodontic patients, limitations of the algorithms, lack of labelled data, high compute power, etc.
Source: Seminars in Orthodontics - Category: Dentistry Authors: Source Type: research