Analysis of 3D Urticaceae Pollen Classification Using Deep Learning Models

Tijs Konijn, Imaan Bijl, Lu Cao, Fons Verbeek

2025

Abstract

Due to the climate change, hay fever becomes a pressing healthcare problem with an increasing number of affected population, prolonged period of affect and severer symptoms. A precise pollen classification could help monitor the trend of allergic pollen in the air throughout the year and guide preventive strategies launched by municipalities. Most of the pollen classification works use 2D microscopy image or 2D projection derived from 3D image datasets. In this paper, we aim at using whole stack of 3D images for the classification and evaluating the classification performance with different deep learning models. The 3D image dataset used in this paper is from Urticaceae family, particularly the genera Urtica and Parietaria, which are morphologically similar yet differ significantly in allergenic potential. The pre-trained ResNet3D model, using optimal layer selection and extended epochs, achieved the best performance with an F1-score of 98.3%.

Paper Citation

in Harvard Style

Konijn T., Bijl I., Cao L. and Verbeek F. (2025). Analysis of 3D Urticaceae Pollen Classification Using Deep Learning Models. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING; ISBN 978-989-758-731-3, SciTePress, pages 288-295. DOI: 10.5220/0013102700003911

in Bibtex Style

@conference{bioimaging25,
author={Tijs Konijn and Imaan Bijl and Lu Cao and Fons Verbeek},
title={Analysis of 3D Urticaceae Pollen Classification Using Deep Learning Models},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING},
year={2025},
pages={288-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013102700003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING
TI - Analysis of 3D Urticaceae Pollen Classification Using Deep Learning Models
SN - 978-989-758-731-3
AU - Konijn T.
AU - Bijl I.
AU - Cao L.
AU - Verbeek F.
PY - 2025
SP - 288
EP - 295
DO - 10.5220/0013102700003911
PB - SciTePress