Landmark annotation through feature combinations: a comparative study on cephalometric images with in-depth analysis of model's explainability

The objectives of this study are to explore and evaluate the automation of anatomical landmark localization in cephalometric images using machine learning techniques, with a focus on feature extraction and combinations, contextual analysis, and model interpretability through Shapley Additive exPlana...

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Veröffentlicht in:	Dento-maxillo-facial radiology 2024-02, Vol.53 (2), p.115-126
Hauptverfasser:	S, Rashmi, S, Srinath, S Murthy, Prashanth, Deshmukh, Seema
Format:	Artikel
Sprache:	eng
Schlagworte:	Anatomic Landmarks Cephalometry - methods Data Curation Humans Machine Learning
Online-Zugang:	Volltext
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