Artificial intelligence models for clinical usage in dentistry with a focus on dentomaxillofacial CBCT: a systematic review
S Mureșanu, O Almășan, M Hedeșiu, L Dioșan… - Oral Radiology, 2023 - Springer
This study aimed at performing a systematic review of the literature on the application of
artificial intelligence (AI) in dental and maxillofacial cone beam computed tomography …
artificial intelligence (AI) in dental and maxillofacial cone beam computed tomography …
The use of cone‐beam computed tomography in management of patients requiring dental implants: an American Academy of Periodontology best evidence review
HF Rios, WS Borgnakke… - Journal of …, 2017 - Wiley Online Library
Background: Application of cone‐beam computed tomography (CBCT) has grown
exponentially across dentistry with a clear impact in implant dentistry. This review aims at …
exponentially across dentistry with a clear impact in implant dentistry. This review aims at …
Deep learning method for mandibular canal segmentation in dental cone beam computed tomography volumes
J Jaskari, J Sahlsten, J Järnstedt, H Mehtonen… - Scientific reports, 2020 - nature.com
Accurate localisation of mandibular canals in lower jaws is important in dental implantology,
in which the implant position and dimensions are currently determined manually from 3D CT …
in which the implant position and dimensions are currently determined manually from 3D CT …
Automatic mandibular canal detection using a deep convolutional neural network
The practicability of deep learning techniques has been demonstrated by their successful
implementation in varied fields, including diagnostic imaging for clinicians. In accordance …
implementation in varied fields, including diagnostic imaging for clinicians. In accordance …
Deep segmentation of the mandibular canal: a new 3D annotated dataset of CBCT volumes
Inferior Alveolar Nerve (IAN) canal detection has been the focus of multiple recent works in
dentistry and maxillofacial imaging. Deep learning-based techniques have reached …
dentistry and maxillofacial imaging. Deep learning-based techniques have reached …
Improving segmentation of the inferior alveolar nerve through deep label propagation
Many recent works in dentistry and maxillofacial imagery focused on the Inferior Alveolar
Nerve (IAN) canal detection. Unfortunately, the small extent of available 3D maxillofacial …
Nerve (IAN) canal detection. Unfortunately, the small extent of available 3D maxillofacial …
Automatic segmentation of mandible from conventional methods to deep learning—a review
B Qiu, H van der Wel, J Kraeima, HH Glas… - Journal of personalized …, 2021 - mdpi.com
Medical imaging techniques, such as (cone beam) computed tomography and magnetic
resonance imaging, have proven to be a valuable component for oral and maxillofacial …
resonance imaging, have proven to be a valuable component for oral and maxillofacial …
Canal-Net for automatic and robust 3D segmentation of mandibular canals in CBCT images using a continuity-aware contextual network
The purpose of this study was to propose a continuity-aware contextual network (Canal-Net)
for the automatic and robust 3D segmentation of the mandibular canal (MC) with high …
for the automatic and robust 3D segmentation of the mandibular canal (MC) with high …
Dual-stage deeply supervised attention-based convolutional neural networks for mandibular canal segmentation in CBCT scans
Accurate segmentation of mandibular canals in lower jaws is important in dental
implantology. Medical experts manually determine the implant position and dimensions from …
implantology. Medical experts manually determine the implant position and dimensions from …
[HTML][HTML] Accuracy of artificial intelligence in the detection and segmentation of oral and maxillofacial structures using cone-beam computed tomography images: a …
F Abesi, AS Jamali, M Zamani - Polish Journal of Radiology, 2023 - ncbi.nlm.nih.gov
Purpose The aim of the present systematic review and meta-analysis was to resolve the
conflicts on the diagnostic accuracy of artificial intelligence systems in detecting and …
conflicts on the diagnostic accuracy of artificial intelligence systems in detecting and …