Teeth numbers and names
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Understanding Teeth Numbers and Names: A Comprehensive Overview
Introduction to Tooth Numbering Systems
Tooth numbering systems are essential for dental professionals to accurately identify and communicate about specific teeth. Various systems have been developed over the years, each with its own method of denoting teeth in both permanent and deciduous (primary) dentitions. This article explores the most common tooth numbering systems and their applications.
Common Tooth Numbering Systems
Universal Numbering System
The Universal Numbering System is widely used in the United States. It assigns a unique number to each tooth, starting from the upper right third molar (tooth 1) and moving sequentially to the upper left third molar (tooth 16), then descending to the lower left third molar (tooth 17) and ending at the lower right third molar (tooth 32)6. For primary teeth, the system uses uppercase letters A through T, starting from the upper right second molar (A) to the lower right second molar (T)6.
Palmer/Zsigmondy Notation
The Palmer Notation, also known as the Zsigmondy system, divides the mouth into four quadrants. Each tooth is assigned a number from 1 to 8, starting from the central incisor to the third molar within each quadrant. The quadrant is indicated by a specific symbol (┘, └, ┐, ┌)3 7. This system is particularly useful for orthodontic and surgical procedures but can be cumbersome for digital documentation3.
Federation Dentaire Internationale (FDI) Two-Digit System
The FDI system, also known as the ISO system, uses a two-digit code to identify each tooth. The first digit represents the quadrant and the type of dentition (1-4 for permanent teeth and 5-8 for primary teeth), while the second digit indicates the tooth's position within the quadrant (1-8 for permanent teeth and 1-5 for primary teeth)3 7. This system is globally recognized and facilitates clear communication between dental professionals3.
Innovative Tooth Numbering Systems
TT (Tikku and Tikku) System
The TT system was developed to simplify tooth numbering for both dental professionals and patients. It uses a straightforward approach that is easy to understand and reduces the risk of misinterpretation. This system is designed to be intuitive, making it accessible for non-dental professionals as well4.
Sarjeev's Supernumerary Tooth Notation System
Sarjeev's system addresses the identification of supernumerary teeth, which are extra teeth that can appear in addition to the regular set. This system integrates with the FDI two-digit system and provides specific notations for different types of supernumerary teeth, such as paramolar, distomolar, and mesiodens, enhancing the clarity and precision of dental records7 10.
Automated Tooth Numbering in Radiographs
Bayesian Classification and Support Vector Machines
Recent advancements in dental imaging have led to the development of algorithms that classify and number teeth in radiographs. Techniques such as Bayesian classification and support vector machines (SVM) use features like tooth contours and spatial relations to accurately identify and number teeth in bitewing and panoramic radiographs2 5. These methods have shown high accuracy rates, making them valuable tools for automated dental identification systems2 5.
Convolutional Neural Networks (CNNs)
Convolutional neural networks (CNNs) have been employed to automate the detection and numbering of teeth in panoramic radiographs. These systems achieve performance metrics comparable to expert-level accuracy, significantly improving the efficiency and completeness of digital dental records8.
Conclusion
Tooth numbering systems are crucial for effective dental practice and communication. While traditional systems like the Universal, Palmer, and FDI systems remain widely used, innovative approaches such as the TT system and Sarjeev's notation for supernumerary teeth offer enhanced simplicity and precision. Additionally, advancements in automated tooth numbering using machine learning algorithms promise to further streamline dental diagnostics and record-keeping. Understanding these systems ensures accurate identification and treatment planning, ultimately benefiting both dental professionals and patients.
Sources and full results
Most relevant research papers on this topic
A new system for denoting tooth
This new system for identifying and recording teeth is simple and accurate, using T and t characters for permanent and deciduous teeth respectively.
Classification and numbering of teeth in dental bitewing images
Our algorithm accurately classifies and assigns numbers to teeth in dental bitewing images using Bayesian classification and Fourier descriptors.
Highly Cited[Standardization of the tooth numbering systems].
The FDI two-digit system is more suitable for dental offices, as it prevents errors and is compatible with computer languages.
'TT' (Tikku and Tikku) system: A simple and novel tooth numbering system for permanent and deciduous teeth
The 'TT' tooth numbering system is a simple, self-reflecting, and user-friendly system that includes patients' perspectives and can be implemented for clinical and forensic applications.
An effective classification and numbering system for dental bitewing radiographs using teeth region and contour information
Our dental classification and numbering system accurately segments, classifies, and numbers teeth in dental bitewing radiographs, with accuracy rates of 95.1% and 98.0%, respectively.
Highly CitedTooth numbering systems.
Tooth numbering systems for primary and deciduous teeth are similar to permanent tooth numbering systems, except that primary teeth are numbered using lower case letters A through T, while deciduous teeth are numbered using upper case letters A through T.
Sarjeev's supernumerary tooth notation system: a universally compatible add-on to the Two-Digit system.
Sarjeev's supernumerary tooth notation system is a universally compatible add-on to the Two-Digit system, providing information on supernumerary teeth for both permanent and deciduous dentition.
Tooth detection and numbering in panoramic radiographs using convolutional neural networks.
The proposed convolutional neural networks-based solution for automatic teeth detection and numbering in dental radiographs performs similarly to experts, offering potential for practical application and improved efficiency in digital dental chart filling.
Highly CitedAssociation between residual teeth number in later life and incidence of dementia: A systematic review and meta-analysis
A higher number of residual teeth in later life is associated with a reduced risk of dementia by approximately 50%, despite limited scientific strength.
Meta-Analysis
Very Rigorous JournalIdentification of supernumerary teeth in 2D and 3D: review of literature and a proposal.
This paper proposes a guideline for locating and identifying supernumerary teeth in 2D and 3D, potentially reducing treatment errors and improving communication among healthcare providers and third-party administrators.
Literature Review