@article{Hoffmann2023,
author = {S. A. Hoffmann and D. Bhattacharya and B. Becker and D. Beyersdorff and E. Petersen and M. Petersen and D. Eggert and A. Schläfer and C. Betz},
title = {Analysing the feasibility of an automated AI-based classifier for detecting paranasal anomalies in the maxillary sinus.},
year = {2023},
volume = {102.},
number = {(S 02),},
publisher = {Georg Thieme Verlag:},
doi = {10.1055/s-0043-1767093},
url = {http://www.thieme-connect.com/products/ejournals/abstract/10.1055/s-0043-1767093},
abstract = {Large scale population studies have been performed to analyse the rate of finding sinus opacities in cranial MRIs. It is of interest whether there are findings requiring clarification. Using AI-based methods can automate the detection of the sinus opacities and reduce the workload of clinicians. In this work, a method for AI-based classification was developed in order to automatically recognise paranasal sinus opacities.}
}

@COMMENT{Bibtex file generated on 2026-7-16 with typo3 si_bibtex plugin. Data from https://www.tuhh.de/mtec/publications/2024-2020 }