Self-CephaloNet: a two-stage novel framework using operational neural network for cephalometric analysis

Self-CephaloNet: a two-stage novel framework using operational neural network for cephalometric analysis

<p dir="ltr">Cephalometric analysis is essential for the diagnosis and treatment planning of orthodontics. In lateral cephalograms, however, the manual detection of anatomical landmarks is a time-consuming procedure. Deep learning solutions hold the potential to address the time cons...

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Bibliographic Details
Main Author: Md. Shaheenur Islam Sumon (17983810) (author)
Other Authors: Khandaker Reajul Islam (16904832) (author), Sakib Abrar Hossain (21980294) (author), Tanzila Rafique (22392142) (author), Ranjit Ghosh (22392145) (author), Gazi Shamim Hassan (22392148) (author), Kanchon Kanti Podder (19459564) (author), Noha Barhom (14150748) (author), Faleh Tamimi (2867255) (author), Muhammad E. H. Chowdhury (14150526) (author)
Published: 2025
Subjects:
Biomedical and clinical sciences
Dentistry
Health sciences
Health services and systems
Self-CephaloNet
Orthodontic diagnosis
Anatomical landmarks
Treatment planning
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