A hierarchical deep learning approach for diagnosing impacted canine-induced root resorption via cone-beam computed tomography
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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A hierarchical deep learning approach for diagnosing impacted canine-induced root resorption via cone-beam computed tomography ; volume:24 ; number:1 ; day:23 ; month:8 ; year:2024 ; pages:1-11 ; date:12.2024
BMC oral health ; 24, Heft 1 (23.8.2024), 1-11, 12.2024
- Creator
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Pirayesh, Zeynab
Mohammad-Rahimi, Hossein
Motamedian, Saeed Reza
Amini Afshar, Sepehr
Abbasi, Reza
Rohban, Mohammad Hossein
Mahdian, Mina
Ghazizadeh Ahsaie, Mitra
Iranparvar Alamdari, Mina
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/s12903-024-04718-4
- URN
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urn:nbn:de:101:1-2411120856135.845721125094
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:30 AM CEST
Data provider
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Associated
- Pirayesh, Zeynab
- Mohammad-Rahimi, Hossein
- Motamedian, Saeed Reza
- Amini Afshar, Sepehr
- Abbasi, Reza
- Rohban, Mohammad Hossein
- Mahdian, Mina
- Ghazizadeh Ahsaie, Mitra
- Iranparvar Alamdari, Mina
- SpringerLink (Online service)
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Predictive factors associated with adjacent teeth root resorption of palatally impacted canines in Arabian population: a cone-beam computed tomography analysis
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Risk prediction model of impacted supernumerary tooth-associated root resorption in children based on cone-beam computed tomography analysis: a case control study
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Three dimensional movement analysis of maxillary impacted canine using TADs: a pilot study
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