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Radiography, Panoramic

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Comparison of 3 deep learning neural networks for classifying the relationship between the mandibular third molar and the mandibular canal on panoramic radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The aim of this study was to compare time and storage space requirements, diagnostic performance, and consistency among 3 image recognition convolutional neural networks (CNNs) in the evaluation of the relationships between the mandibular ...

Towards fully automated third molar development staging in panoramic radiographs.

International journal of legal medicine
Staging third molar development is commonly used for age assessment in sub-adults. Current staging techniques are, at most, semi-automated and rely on manual interactions prone to operator variability. The aim of this study was to fully automate the ...

DeNTNet: Deep Neural Transfer Network for the detection of periodontal bone loss using panoramic dental radiographs.

Scientific reports
In this study, a deep learning-based method for developing an automated diagnostic support system that detects periodontal bone loss in the panoramic dental radiographs is proposed. The presented method called DeNTNet not only detects lesions but als...

Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network.

Oral diseases
OBJECTIVES: The aim of the current study was to evaluate the detection and diagnosis of three types of odontogenic cystic lesions (OCLs)-odontogenic keratocysts, dentigerous cysts, and periapical cysts-using dental panoramic radiography and cone beam...

Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: To evaluate a fully deep learning mask region-based convolutional neural network (R-CNN) method for automated tooth segmentation using individual annotation of panoramic radiographs.

Convolutional neural networks for dental image diagnostics: A scoping review.

Journal of dentistry
OBJECTIVES: Convolutional neural networks (CNNs) are increasingly applied for medical image diagnostics. We performed a scoping review, exploring (1) use cases, (2) methodologies and (3) findings of studies applying CNN on dental image material.

Effect of Lower Third Molar Segmentations on Automated Tooth Development Staging using a Convolutional Neural Network.

Journal of forensic sciences
Staging third molar development is commonly used for age estimation in subadults. Automated developmental stage allocation to the mandibular left third molar in panoramic radiographs has been examined in a pilot study. This method used an AlexNet Dee...

The missing link in image quality assessment in digital dental radiography.

Oral radiology
Digital radiography is gaining popularity among general dental practitioners. It includes digital intraoral radiography, digital panoramic radiography, digital cephalography, and cone-beam computed tomography. In this study, we focused on the methods...

Automated detection of third molars and mandibular nerve by deep learning.

Scientific reports
The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a risk factor for the occurrence of nerve damage and subsequent sensory disturbances of the lower lip and chin following the removal of third molars. To a...

Automatic detection and classification of radiolucent lesions in the mandible on panoramic radiographs using a deep learning object detection technique.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The aim of this study was to investigate whether a deep learning object detection technique can automatically detect and classify radiolucent lesions in the mandible on panoramic radiographs.