Computational Intelligence and Augmented Reality in Stomatology

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064203%3A_____%2F25%3A10510589" target="_blank" >RIV/00064203:_____/25:10510589 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11110/25:10510589 RIV/00216208:11130/25:10510589 RIV/00216208:11150/25:10510589

Výsledek na webu

<a href="https://doi.org/10.1002/9781394302864.ch7" target="_blank" >https://doi.org/10.1002/9781394302864.ch7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/9781394302864.ch7" target="_blank" >10.1002/9781394302864.ch7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Computational Intelligence and Augmented Reality in Stomatology

Popis výsledku v původním jazyce

Computational intelligence and augmented reality in stomatology form a specific area based on the use of general digital signal and image processing methods in dentistry. Associated methods allow the transition from traditional plaster cast examination to digital and three-dimensional (3D) modeling of dental objects, mathematical analysis of dental tissue disorders, and objective evaluation of the treatment progress. It delves into how machine learning, especially deep learning and convolutional neural networks, revolutionizes the identification of stomatological disorders and the classification of dental caries through the construction of sophisticated mathematical models. Highlighting a range of digital techniques employed in the field, the review focuses on the adoption of intra-oral scanning technology for precise data capturing and analysis of dental arches&apos; key characteristics. It also examines computational methods for analyzing reflectivity data to differentiate between healthy tissues and caries, leveraging deep learning for enhanced accuracy. Furthermore, the chapter covers augmented reality&apos;s role in dental medicine, showcasing its utility in signal processing, morphological analysis of spatial objects, and monitoring treatment progress through detailed 3D models. These models facilitate the comparison of dental arch shapes and positions over time, offering a digital alternative to physical casts for semi-automatic evaluation of dental metrics. Additionally, it underscores computational intelligence&apos;s potential in assessing dental tissue reflectivity, opening new avenues for non-invasive diagnosis of dental issues. Conclusively, the study affirms the significant advantages of 3D digital technologies over traditional methods in stomatology, proving how a broad interdisciplinary collaboration, artificial intelligence, and deep learning can significantly enhance diagnostic processes and treatment outcomes in dental care.

Název v anglickém jazyce

Computational Intelligence and Augmented Reality in Stomatology

Popis výsledku anglicky

Computational intelligence and augmented reality in stomatology form a specific area based on the use of general digital signal and image processing methods in dentistry. Associated methods allow the transition from traditional plaster cast examination to digital and three-dimensional (3D) modeling of dental objects, mathematical analysis of dental tissue disorders, and objective evaluation of the treatment progress. It delves into how machine learning, especially deep learning and convolutional neural networks, revolutionizes the identification of stomatological disorders and the classification of dental caries through the construction of sophisticated mathematical models. Highlighting a range of digital techniques employed in the field, the review focuses on the adoption of intra-oral scanning technology for precise data capturing and analysis of dental arches&apos; key characteristics. It also examines computational methods for analyzing reflectivity data to differentiate between healthy tissues and caries, leveraging deep learning for enhanced accuracy. Furthermore, the chapter covers augmented reality&apos;s role in dental medicine, showcasing its utility in signal processing, morphological analysis of spatial objects, and monitoring treatment progress through detailed 3D models. These models facilitate the comparison of dental arch shapes and positions over time, offering a digital alternative to physical casts for semi-automatic evaluation of dental metrics. Additionally, it underscores computational intelligence&apos;s potential in assessing dental tissue reflectivity, opening new avenues for non-invasive diagnosis of dental issues. Conclusively, the study affirms the significant advantages of 3D digital technologies over traditional methods in stomatology, proving how a broad interdisciplinary collaboration, artificial intelligence, and deep learning can significantly enhance diagnostic processes and treatment outcomes in dental care.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

30208 - Dentistry, oral surgery and medicine

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Augmented and Virtual Reality in Immersive Healthcare

ISBN

978-1-394-30283-3

Počet stran výsledku

32

Strana od-do

175-206

Počet stran knihy

576

Název nakladatele

Scrivener Publishing

Místo vydání

Beverly

Kód UT WoS kapitoly

—