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Shinta Amini Prativi on Muck Rack

Shinta Amini Prativi

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Articles

Development of a YOLOv9 model with angle loss for automatic detection of landmarks and cephalometric analysis

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By Andriyan Suksmono, Akira Hirose, Stefanie Mueller, Shinta Amini Prativi, Donny Danudirdjo
| Nature Verified
Abstract Artificial intelligence has been widely applied to identify anatomical landmarks on lateral cephalometric radiographs, reducing localization errors and improving the efficiency of cephalometric analysis. This study aimed to develop and evaluate an automated cephalometric landmark detection system based on You Only Look Once version 9 (YOLOv9) with an angle-based loss function and automated Steiner cephalometric analysis using radiographs from an Indonesian population.
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