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

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

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.

• Jezik: Angleški jezik
• Ključne besede: medical image analysis, assignment theory, dental cast, geometry, labeling, deep neural networks
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FE - Fakulteta za elektrotehniko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2025
• Št. strani: Str. 4981-4990
• Številčenje: Vol. 29, no. 9
• PID: 20.500.12556/RUL-178287
• UDK: 004.93:61
• ISSN pri članku: 2168-2208
• DOI: 10.1109/JBHI.2025.3549685
• COBISS.SI-ID: 230531587
• Datum objave v RUL: 22.01.2026

Gradivo je del revije

• Naslov: IEEE journal of biomedical and health informatics
• Skrajšan naslov: IEEE j. biomed. health inform.
• Založnik: Institute of Electrical and Electronics Engineers
• ISSN: 2168-2208
• COBISS.SI-ID: 17173014

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: analiza medicinskih slik, teorija dodeljevanje, zobni odlitek, geometrija, označevanje, globoke nevronske mreže

Projekti

• Financer: Drugi - Drug financer ali več financerjev
• Program financ.: University of Copenhagen
• Številka projekta: -
• Naslov: Data+ grant

• Financer: ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
• Številka projekta: P2-0232
• Naslov: Analiza biomedicinskih slik in signalov