• The development of an image pr...

*Result*: The development of an image processing model to estimate tooth width and space requirements.

Title:
The development of an image processing model to estimate tooth width and space requirements.
Authors:
Toner R; School of Dental Science, Dublin Dental University Hospital, University of Dublin, Trinity College Dublin, Dublin, Ireland. Electronic address: rebecca_toner@hotmail.co.uk., Eribo M; School of Dental Science, Dublin Dental University Hospital, University of Dublin, Trinity College Dublin, Dublin, Ireland., Honari B; School of Dental Science, Dublin Dental University Hospital, University of Dublin, Trinity College Dublin, Dublin, Ireland., Daly K; Northern Cross Dental, Dublin, Dublin 17, Ireland., Fleming PS; School of Dental Science, Dublin Dental University Hospital, University of Dublin, Trinity College Dublin, Dublin, Ireland; Queen Mary University London, London, UK.
Source:
Journal of dentistry [J Dent] 2026 Mar; Vol. 166, pp. 106330. Date of Electronic Publication: 2026 Jan 03.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: England NLM ID: 0354422 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-176X (Electronic) Linking ISSN: 03005712 NLM ISO Abbreviation: J Dent Subsets: MEDLINE
Imprint Name(s):
Publication: Kidlington : Elsevier
Original Publication: Bristol, Eng., Wright.
MeSH Terms:
Image Processing, Computer-Assisted*/methods , Malocclusion*/diagnostic imaging , Malocclusion*/therapy , Tooth*/anatomy & histology , Tooth*/diagnostic imaging , Odontometry*/methods, Dental Arch/anatomy & histology ; Dental Arch/diagnostic imaging ; Humans ; Models, Dental ; Reproducibility of Results ; Deep Learning ; Observer Variation ; Female ; Male
Contributed Indexing:
Keywords: AI; Artificial intelligence; Orthodontics; Space analysis; Treatment planning
Entry Date(s):
Date Created: 20260106 Date Completed: 20260206 Latest Revision: 20260206
Update Code:
20260207
DOI:
10.1016/j.jdent.2026.106330
PMID:
41491146
Database:
MEDLINE

*Further Information*

*Objectives: The advent of machine and deep learning has raised the possibility of increased efficiency and indeed improved accuracy in relation to the interpretation of clinical images. Moreover, the use of deep learning has become imbedded within orthodontics with attempts to utilise this approach in informing treatment planning. The aim of this study was to develop and test an AI-based tool capable of measuring tooth width and dental crowding.
Methodology: Sets of pre and post treatment plaster study models were acquired of 245 patients who had treatment completed in a specialist orthodontic practice by a single orthodontist. These models were scanned to create stereolithography (STL) files. These files were used to train an AI tool capable of calculating the mesio-distal widths of each of the teeth in the arches. To test the validity of this model, direct comparison was made between the AI tool and human raters. A sample of twelve sets of pre-treatment study models were known as the "test data". The test data was analysed by a group of five orthodontic clinicians at two separate time intervals 6 weeks apart.
Results: Statistical analysis confirmed a high level of agreement between human raters and also in relation to the novel AI-based tool. Inter-rater reliability among the human raters was high with Intraclass correlation coefficients (ICCs) ranging from 0.911 to 0.946 between the intervals. Manual measurements also demonstrated a high level of agreement with the AI tool (ICC= 0.956; Mean absolute difference= 0.4 mm).
Conclusions: The novel AI-based tool demonstrated reliability in calculating mesiodistal widths of teeth in an untreated arch. This tool will be further developed to incorporate other parameters such as arch levelling, to provide a means to calculate the overall space requirement within the dental arches.
(Copyright © 2026 Elsevier Ltd. All rights reserved.)*

*Declaration of competing interest The authors declare no competing interests. Given their role as an Associate Editor, Padhraig S. Fleming had no involvement in the peer review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was taken by another journal editor.*