Virtual Reality Haptic Simulation of Root Canal Therapy

Toosi, Amirhosein; Arbabtafti, Mohammadreza; Richardson, Barry Lund

doi:10.4028/www.scientific.net/amm.666.388

Cited by 8 publications

(4 citation statements)

References 12 publications

(14 reference statements)

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“…A robot called the “Omni Phantom,” with a haptic virtual reality simulator has been developed to help users efficiently train in endodontic procedures. Using a simulated K-file, the user can experience the process of burring the enamel and dentin and cleaning the inner surface of the root canal [ 11 ]. Razavi et al proposed a new approach to calculate the feedback force, and the speed of haptic loop execution increased approximately eight times in the process of a haptics-based tooth-drilling simulation [ 12 ].…”

Section: Resultsmentioning

confidence: 99%

Robotics in Dentistry: A Narrative Review

2023

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Background: Robotics is progressing rapidly. The aim of this study was to provide a comprehensive overview of the basic and applied research status of robotics in dentistry and discusses its development and application prospects in several major professional fields of dentistry. Methods: A literature search was conducted on databases: MEDLINE, IEEE and Cochrane Library, using MeSH terms: [“robotics” and “dentistry”]. Result: Forty-nine articles were eventually selected according to certain inclusion criteria. There were 12 studies on prosthodontics, reaching 24%; 11 studies were on dental implantology, accounting for 23%. Scholars from China published the most articles, followed by Japan and the United States. The number of articles published between 2011 and 2015 was the largest. Conclusions: With the advancement of science and technology, the applications of robots in dental medicine has promoted the development of intelligent, precise, and minimally invasive dental treatments. Currently, robots are used in basic and applied research in various specialized fields of dentistry. Automatic tooth-crown-preparation robots, tooth-arrangement robots, drilling robots, and orthodontic archwire-bending robots that meet clinical requirements have been developed. We believe that in the near future, robots will change the existing dental treatment model and guide new directions for further development.

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Section: Resultsmentioning

confidence: 99%

Robotics in Dentistry: A Narrative Review

2023

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“…Cheng et al [20] obtained the implantation point through an L-shaped intraoral marker, and its transformation is derived to achieve accurate positioning. Toosi et al [21] developed simulation software for a master-slave dental robot using collision detection. On the other hand, master-slave control and cooperative control are commonly adopted.…”

Section: Related Workmentioning

confidence: 99%

A Guiding and Positioning Motion Strategy Based on a New Conical Virtual Fixture for Robot-Assisted Oral Surgery

Wang

Wang²,

Cai³

et al. 2022

Machines

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In robot-assisted oral surgery, the surgical tool needs to be fed into the target position to perform surgery. However, unmodeled extraoral and complex intraoral environments bring difficulties to motion planning. Meanwhile, the motion is operated manually by the surgeon, causing relatively limited accuracy as well as the risk of misoperation. Moreover, the random movements of the patient’s head bring additional disturbance to the task. To achieve the task, a motion strategy based on a new conical virtual fixture (VF) was proposed. First, by preoperatively specifying a conical guiding cone as the VF, virtual repulsive forces were applied on the out-of-range end effector. Then, based on the two-point adjustment model and velocity conversion, the effect of VF was established to prevent the end-effector from exceeding the constraint region. Finally, a vision system corrects the guiding cone to compensate for the random movement of the patient’s head to feed to a dynamic target. As an auxiliary framework for surgical operation, the proposed strategy has the advantages of safety, accuracy, and dynamic adaptability. Both simulations and experiments are conducted, verifying the feasibility of the proposed strategy.

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“…With the introduction of precise digital machines, dentists can provide high-quality treatment to their patients [1,2]. Various studies have shown that these computer-aided machines help dentists in various ways, from the fabrication of prostheses using CAD/CAM [2][3][4][5] to the use of robots in the treatment of patients [6][7][8]. The introduction of AI has taken dentistry to the next level.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Artificial Intelligence Models in Dental Implant Fixture Identification and Classification from Radiographs: A Systematic Review

Ibraheem

2024

Diagnostics

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Background and Objectives: The availability of multiple dental implant systems makes it difficult for the treating dentist to identify and classify the implant in case of inaccessibility or loss of previous records. Artificial intelligence (AI) is reported to have a high success rate in medical image classification and is effectively used in this area. Studies have reported improved implant classification and identification accuracy when AI is used with trained dental professionals. This systematic review aims to analyze various studies discussing the accuracy of AI tools in implant identification and classification. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study was registered with the International Prospective Register of Systematic Reviews (PROSPERO). The focused PICO question for the current study was “What is the accuracy (outcome) of artificial intelligence tools (Intervention) in detecting and/or classifying the type of dental implant (Participant/population) using X-ray images?” Web of Science, Scopus, MEDLINE-PubMed, and Cochrane were searched systematically to collect the relevant published literature. The search strings were based on the formulated PICO question. The article search was conducted in January 2024 using the Boolean operators and truncation. The search was limited to articles published in English in the last 15 years (January 2008 to December 2023). The quality of all the selected articles was critically analyzed using the Quality Assessment and Diagnostic Accuracy Tool (QUADAS-2). Results: Twenty-one articles were selected for qualitative analysis based on predetermined selection criteria. Study characteristics were tabulated in a self-designed table. Out of the 21 studies evaluated, 14 were found to be at risk of bias, with high or unclear risk in one or more domains. The remaining seven studies, however, had a low risk of bias. The overall accuracy of AI models in implant detection and identification ranged from a low of 67% to as high as 98.5%. Most included studies reported mean accuracy levels above 90%. Conclusions: The articles in the present review provide considerable evidence to validate that AI tools have high accuracy in identifying and classifying dental implant systems using 2-dimensional X-ray images. These outcomes are vital for clinical diagnosis and treatment planning by trained dental professionals to enhance patient treatment outcomes.

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Virtual Reality Haptic Simulation of Root Canal Therapy

Cited by 8 publications

References 12 publications

Robotics in Dentistry: A Narrative Review

Robotics in Dentistry: A Narrative Review

A Guiding and Positioning Motion Strategy Based on a New Conical Virtual Fixture for Robot-Assisted Oral Surgery

Accuracy of Artificial Intelligence Models in Dental Implant Fixture Identification and Classification from Radiographs: A Systematic Review

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