DentAssignNet : assignment network for dental cast labeling in the presence of dental abnormalities

Dascalu, Tudor (author), Ramezanzade, Shaqayeq (author), Bakhshandeh, Azam (author), Bjørndal, Lars (author), Iurcov, Raluca (author), Vrtovec, Tomaž (author), Ibragimov, Bulat (author)

This study focuses on the challenging problem of labeling a collection of objects with inherent morphological and positional dependencies, where instances may be missing or duplicated. We integrate principles of assignment theory in the design of a convolutional neural network to find the optimal label set given pairwise geometrical features extracted from the candidate objects. The objective function aims to minimize the distance between the one-hot encoded labels of the objects and the scores produced by the model, with added emphasis on the scores corresponding to the optimal assignment plan. We tested our solution in the dental domain on the task of finding the teeth labels given a set of candidate instances. The study database included 1200 dental casts of upper and lower jaws from 600 patients. The model reached identification accuracies of 0.952 and 0.968 for the lower and upper jaws, respectively. Moreover, we presented a solution for generating teeth candidates using a multi-step pipeline consisting of coarse and fine segmentations. The algorithm was tested on a database consisting of 600 dental casts, reaching an F1 score of 0.968.

• Language: English
• Keywords: medical image analysis, assignment theory, dental cast, geometry, labeling, deep neural networks
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2025
• Number of pages: Str. 4981-4990
• Numbering: Vol. 29, no. 9
• PID: 20.500.12556/RUL-178287
• UDC: 004.93:61
• ISSN on article: 2168-2208
• DOI: 10.1109/JBHI.2025.3549685
• COBISS.SI-ID: 230531587
• Publication date in RUL: 22.01.2026

Record is a part of a journal

• Title: IEEE journal of biomedical and health informatics
• Shortened title: IEEE j. biomed. health inform.
• Publisher: Institute of Electrical and Electronics Engineers
• ISSN: 2168-2208
• COBISS.SI-ID: 17173014

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: analiza medicinskih slik, teorija dodeljevanje, zobni odlitek, geometrija, označevanje, globoke nevronske mreže

Projects

• Funder: Other - Other funder or multiple funders
• Funding programme: University of Copenhagen
• Project number: -
• Name: Data+ grant

• Funder: ARIS - Slovenian Research and Innovation Agency
• Project number: P2-0232
• Name: Analiza biomedicinskih slik in signalov