DeepCellCount: Cell Counting Using Two-Step Deep Learning

Sara Tesfamariam, Isah A. Lawal, Arda Durmaz, Jacob G. Scott

2025

Abstract

This paper addresses the problem of segmenting and counting cells in fluorescent microscopy images. Accurate identification and counting of cells is crucial for automated cell annotation processes in biomedical laboratories. To address this, we trained two convolutional neural networks using publicly available high-throughput microscopy cell image sets. One network is trained for cell segmentation and the other for cell counting. Both models are then used in a two-step image analysis process to identify and count the cells in a given image. We evaluated the performance of this method on previously unseen cell images, and our experimental results show that the proposed method achieved an average Mean Absolute Percentage Error (MAPE) as low as 6.82 on the test images with sparsely populated cells. This performance is comparable to that obtained with a more complex CellProfiler software on the same dataset.

Paper Citation

in Harvard Style

Tesfamariam S., Lawal I., Durmaz A. and Scott J. (2025). DeepCellCount: Cell Counting Using Two-Step Deep Learning. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 980-985. DOI: 10.5220/0013369900003912

in Bibtex Style

@conference{visapp25,
author={Sara Tesfamariam and Isah Lawal and Arda Durmaz and Jacob Scott},
title={DeepCellCount: Cell Counting Using Two-Step Deep Learning},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={980-985},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013369900003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - DeepCellCount: Cell Counting Using Two-Step Deep Learning
SN - 978-989-758-728-3
AU - Tesfamariam S.
AU - Lawal I.
AU - Durmaz A.
AU - Scott J.
PY - 2025
SP - 980
EP - 985
DO - 10.5220/0013369900003912
PB - SciTePress