Intraoral Scanners

Intraoral scanners (IOS) have revolutionized the field of dentistry by providing a noninvasive and efficient means of capturing direct optical impressions of the oral cavity. This article presents an overview of the applications, advantages, and challenges associated with the adoption of intraoral scanners in dental practice. Intraoral scanners allow for the precise measurement of teeth and gum surfaces, offering numerous benefits to both patients and practitioners. By eliminating the need for traditional impression materials, IOS significantly reduces patient discomfort and operator burden, while minimizing the risk of infection transmission. Real-time impression scanning facilitates immediate visualization, simplifying replication, and selective scanning processes. Despite these advantages, there are challenges in the widespread adoption of intraoral scanners. Identification of deep margins in prepared teeth, particularly in cases of bleeding, remains a significant obstacle. Additionally, there is a learning curve associated with mastering IOS techniques, which requires practitioners to invest time and resources in training. This article provides valuable information on the advancements and challenges of intraoral scanners in modern dentistry. By addressing these challenges and leveraging the benefits of IOS, dental professionals can improve patient care, streamline workflows, and improve overall practice efficiency. Keywords: Dentistry, Digital models, Intraoral scanners, Optical impression

Authors

Publication Details

Journal
Clinical Dentistry
Published
2024-09-21
DOI
https://doi.org/10.33882/clinicaldent.15.36951
Primary Topic
Dental materials and restorations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intraoral Scanners

Benley George, Adila Parveen, Rino Roopak Soman
Clinical Dentistry
Dental materials and restorations
article

Intraoral Scanners

Benley George, Adila Parveen, Rino Roopak Soman
article en

Abstract

Intraoral scanners (IOS) have revolutionized the field of dentistry by providing a noninvasive and efficient means of capturing direct optical impressions of the oral cavity. This article presents an overview of the applications, advantages, and challenges associated with the adoption of intraoral scanners in dental practice. Intraoral scanners allow for the precise measurement of teeth and gum surfaces, offering numerous benefits to both patients and practitioners. By eliminating the need for traditional impression materials, IOS significantly reduces patient discomfort and operator burden, while minimizing the risk of infection transmission. Real-time impression scanning facilitates immediate visualization, simplifying replication, and selective scanning processes. Despite these advantages, there are challenges in the widespread adoption of intraoral scanners. Identification of deep margins in prepared teeth, particularly in cases of bleeding, remains a significant obstacle. Additionally, there is a learning curve associated with mastering IOS techniques, which requires practitioners to invest time and resources in training. This article provides valuable information on the advancements and challenges of intraoral scanners in modern dentistry. By addressing these challenges and leveraging the benefits of IOS, dental professionals can improve patient care, streamline workflows, and improve overall practice efficiency. Keywords: Dentistry, Digital models, Intraoral scanners, Optical impression

Clinical Dentistry
Openalex Percentile: Top 69%
Dental materials and restorations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.