Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource, 1 online resource.
- Language
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Englisch
- Bibliographic citation
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Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis ; volume:128 ; number:5 ; day:24 ; month:4 ; year:2023 ; pages:544-555 ; date:5.2023
La Radiologia medica ; 128, Heft 5 (24.4.2023), 544-555, 5.2023
- Creator
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Serafin, Marco
Baldini, Benedetta
Cabitza, Federico
Carrafiello, Gianpaolo
Baselli, Giuseppe
Del Fabbro, Massimo
Sforza, Chiarella
Caprioglio, Alberto
Tartaglia, Gianluca M.
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s11547-023-01629-2
- URN
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urn:nbn:de:101:1-2023090808143306050814
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:52 AM CEST
Data provider
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Associated
- Serafin, Marco
- Baldini, Benedetta
- Cabitza, Federico
- Carrafiello, Gianpaolo
- Baselli, Giuseppe
- Del Fabbro, Massimo
- Sforza, Chiarella
- Caprioglio, Alberto
- Tartaglia, Gianluca M.
- SpringerLink (Online service)
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Development and validation of predictive models for skeletal malocclusion classification using airway and cephalometric landmarks
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Automated detection of cephalometric landmarks using deep neural patchworks
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Evaluating the accuracy of automated cephalometric analysis based on artificial intelligence
Does the FARNet neural network algorithm accurately identify Posteroanterior cephalometric landmarks?
Automated Detection of Cat Facial Landmarks
Accuracy of cephalometric landmark and cephalometric analysis from lateral facial photograph by using CNN-based algorithm
The accuracy of a designed software for automated localization of craniofacial landmarks on CBCT images
Development and validation of predictive models for skeletal malocclusion classification using airway and cephalometric landmarks
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