Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset

Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset

Abstract Preoperative radiological identification of mandibular canals is essential for maxillofacial surgery. This study demonstrates the reproducibility of a deep learning system (DLS) by evaluating its localisation performance on 165 heterogeneous cone beam computed tomography (CBCT) scans from 7...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Jorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski, Helena Mehtonen, Ari Hietanen, Osku Sundqvist, Vesa Varjonen, Vesa Mattila, Sangsom Prapayasatok, Sakarat Nalampang
Format: Artykuł
Język:English
Wydane: Nature Portfolio 2023-08-01
Seria:Scientific Reports
Dostęp online:https://doi.org/10.1038/s41598-023-40516-8

Internet

https://doi.org/10.1038/s41598-023-40516-8

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