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

Abstract 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 v...

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Bibliographic Details
Main Authors: Muhammad Anwaar Khalid, Kanwal Zulfiqar, Ulfat Bashir, Areeba Shaheen, Rida Iqbal, Zarnab Rizwan, Ghina Rizwan, Muhammad Moazam Fraz
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05542-3
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