AIMC Topic: Dental Implants

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Predictive modeling for peri-implantitis by using machine learning techniques.

Scientific reports
The purpose of this retrospective cohort study was to create a model for predicting the onset of peri-implantitis by using machine learning methods and to clarify interactions between risk indicators. This study evaluated 254 implants, 127 with and 1...

A deep learning approach for dental implant planning in cone-beam computed tomography images.

BMC medical imaging
BACKGROUND: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.

Accuracy of dental implant surgery with robotic position feedback and registration algorithm: An in-vitro study.

Computers in biology and medicine
BACKGROUND: The purpose of this study was to develop and validate a positioning method with hand-guiding and contact position feedback of robot based on a human-robot collaborative dental implant system (HRCDIS) for robotic guided dental implant surg...

Trabeculae microstructure parameters serve as effective predictors for marginal bone loss of dental implant in the mandible.

Scientific reports
Marginal bone loss (MBL) is one of the leading causes of dental implant failure. This study aimed to investigate the feasibility of machine learning (ML) algorithms based on trabeculae microstructure parameters to predict the occurrence of severe MBL...

Truncation compensation and metallic dental implant artefact reduction in PET/MRI attenuation correction using deep learning-based object completion.

Physics in medicine and biology
The susceptibility of MRI to metallic objects leads to void MR signal and missing information around metallic implants. In addition, body truncation occurs in MR imaging for large patients who exceed the transaxial field-of-view of the scanner. Body ...

Automatic robot-world calibration in an optical-navigated surgical robot system and its application for oral implant placement.

International journal of computer assisted radiology and surgery
PURPOSE: Robot-world calibration, used to precisely determine the spatial relation between optical tracker and robot, is regarded as an essential step for optical-navigated surgical robot system to improve the surgical accuracy. However, these method...

External validation and transfer learning of convolutional neural networks for computed tomography dental artifact classification.

Physics in medicine and biology
Quality assurance of data prior to use in automated pipelines and image analysis would assist in safeguarding against biases and incorrect interpretation of results. Automation of quality assurance steps would further improve robustness and efficienc...

Automatic classification of dental artifact status for efficient image veracity checks: effects of image resolution and convolutional neural network depth.

Physics in medicine and biology
Enabling automated pipelines, image analysis and big data methodology in cancer clinics requires thorough understanding of the data. Automated quality assurance steps could improve the efficiency and robustness of these methods by verifying possible ...

Robotics in Dental Implantology.

Oral and maxillofacial surgery clinics of North America
Robotic surgery is no longer a fiction and its clinical applications are rapidly developing. Robotic surgery is increasingly used because of its minimal invasiveness. This article provides an overview of robotic surgery and its current applications i...

Uncertainty optimization of dental implant based on finite element method, global sensitivity analysis and support vector regression.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
In this work, an uncertainty optimization approach for dental implant is proposed to reduce the stress at implant-bone interface. Finite element method is utilized to calculate the stress at implant-bone interface, and support vector regression is us...