AIMC Topic: Dental Implants

Clear Filters Showing 51 to 60 of 112 articles

Deep learning and clustering approaches for dental implant size classification based on periapical radiographs.

Scientific reports
This study investigated two artificial intelligence (AI) methods for automatically classifying dental implant diameter and length based on periapical radiographs. The first method, deep learning (DL), involved utilizing the pre-trained VGG16 model an...

Dental implant brand and angle identification using deep neural networks.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Determining the brand and angle of an implant clinically or radiographically can be challenging. Whether artificial intelligence can assist is unclear.

Performance evaluation of deep learning models for the classification and identification of dental implants.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Dental implant systems can be identified using image classification deep learning. However, investigations on the accuracy of classifying and identifying implant design through an object detection model are lacking.

Semi-autonomous two-stage dental robotic technique for zygomatic implants: An in vitro study.

Journal of dentistry
OBJECTIVE: To assess the feasibility and accuracy of a semi-autonomous two-stage dental robotic technique for zygomatic implants.

The CNN model aided the study of the clinical value hidden in the implant images.

Journal of applied clinical medical physics
PURPOSE: This article aims to construct a new method to evaluate radiographic image identification results based on artificial intelligence, which can complement the limited vision of researchers when studying the effect of various factors on clinica...

Robot assisted implant surgery: Hype or hope?

Journal of stomatology, oral and maxillofacial surgery
The 21st century is characterized by accelerated technological innovation, resulting in digitization of most areas of medicine and dentistry. Dental implant surgical planning has evolved from using analog static guides to computer generated guides an...

Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study.

Journal of dentistry
OBJECTIVES: To train and validate a cloud-based convolutional neural network (CNN) model for automated segmentation (AS) of dental implant and attached prosthetic crown on cone-beam computed tomography (CBCT) images.

Accuracy and efficiency of robotic dental implant surgery with different human-robot interactions: An in vitro study.

Journal of dentistry
OBJECTIVES: This study aims to compare the surgical efficiency (preparation and operation time) and accuracy of implant placement between robots with different human-robot interactions.

Accuracy and safety of a haptic operated and machine vision controlled collaborative robot for dental implant placement: A translational study.

Clinical oral implants research
OBJECTIVES: Multiple generations of medical robots have revolutionized surgery. Their application to dental implants is still in its infancy. Co-operating robots (cobots) have great potential to improve the accuracy of implant placement, overcoming t...