A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification

• Published in: Scientific data Vol. 12; no. 1; pp. 1336 - 13
• Main Authors: Khalid, Muhammad Anwaar, Zulfiqar, Kanwal, Bashir, Ulfat, Shaheen, Areeba, Iqbal, Rida, Rizwan, Zarnab, Rizwan, Ghina, Fraz, Muhammad Moazam
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 31.07.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 692/53/2421; 692/698/3008; Anatomic Landmarks - diagnostic imaging; Annotations; Artificial intelligence; Automation; Benchmarking; Cephalometry; Cervical Vertebrae - diagnostic imaging; Cervical Vertebrae - growth & development; Classification; Data Descriptor; Datasets; Humanities and Social Sciences; Humans; Localization; Medical diagnosis; multidisciplinary; Orthodontics; Science; Science (multidisciplinary); Vertebrae

Accurate identification and localization of cephalometric landmarks are crucial for diagnosing and quantifying anatomical abnormalities in orthodontics. Traditional manual annotation of these landmarks on lateral cephalograms (LCRs) is time-consuming and subject to inter- and intra-expert variabilit...