AIMC Topic: Cone-Beam Computed Tomography

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Exploring the potential of artificial intelligence in paediatric dentistry: A systematic review on deep learning algorithms for dental anomaly detection.

International journal of paediatric dentistry
BACKGROUND: Artificial intelligence (AI) based on deep learning (DL) algorithms has shown promise in enhancing the speed and accuracy of dental anomaly detection in paediatric dentistry.

Robot-Assisted and Haptic-Guided Endodontic Surgery: A Case Report.

Journal of endodontics
There has been a significant increase in robot-assisted dental procedures in the past decade, particularly in the area of robot-assisted implant placement. The objective of this case report was to assess the initial use of the Yomi Robot's assistance...

Effect of implant shape and length on the accuracy of robot-assisted immediate implant surgery: An in vitro study.

Clinical oral implants research
OBJECTIVES: To compare the accuracy of immediate implant placement of cylindrical implants (CI) and tapered implants (TI) of different lengths using a robotic dental implant system.

Deep learning driven segmentation of maxillary impacted canine on cone beam computed tomography images.

Scientific reports
The process of creating virtual models of dentomaxillofacial structures through three-dimensional segmentation is a crucial component of most digital dental workflows. This process is typically performed using manual or semi-automated approaches, whi...

Full virtual patient generated by artificial intelligence-driven integrated segmentation of craniomaxillofacial structures from CBCT images.

Journal of dentistry
OBJECTIVES: To assess the performance, time-efficiency, and consistency of a convolutional neural network (CNN) based automated approach for integrated segmentation of craniomaxillofacial structures compared with semi-automated method for creating a ...

Super-resolution dual-layer CBCT imaging with model-guided deep learning.

Physics in medicine and biology
This study aims at investigating a novel super resolution CBCT imaging approach with a dual-layer flat panel detector (DL-FPD).With DL-FPD, the low-energy and high-energy projections acquired from the top and bottom detector layers contain over-sampl...

Convolutional neural network-assisted diagnosis of midpalatal suture maturation stage in cone-beam computed tomography.

Journal of dentistry
OBJECTIVES: The selection of treatment for maxillary expansion is closely related to the calcification degree of the midpalatal suture. A classification method for individual assessment of the morphology of midpalatal suture in cone-beam computed tom...

Automatic diagnosis of true proximity between the mandibular canal and the third molar on panoramic radiographs using deep learning.

Scientific reports
Evaluating the mandibular canal proximity is crucial for planning mandibular third molar extractions. Panoramic radiography is commonly used for radiological examinations before third molar extraction but has limitations in assessing the true contact...

Accuracy of an optical robotic computer-aided implant system and the trueness of virtual techniques for measuring robot accuracy evaluated with a coordinate measuring machine in vitro.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: A unified standard for measuring robot implantation errors has not yet been established. A coordinate measuring machine (CMM) measures the coordinates of an object with high accuracy. However, evaluations of the accuracy of a ro...

Deep learning-based automatic segmentation of bone graft material after maxillary sinus augmentation.

Clinical oral implants research
OBJECTIVES: To investigate the accuracy and reliability of deep learning in automatic graft material segmentation after maxillary sinus augmentation (SA) from cone-beam computed tomography (CBCT) images.