Counting or Localizing? Evaluating Cell Counting and Detection in Microscopy Images

Luca Ciampi, Fabio Carrara, Giuseppe Amato, Claudio Gennaro

2022

Abstract

Image-based automatic cell counting is an essential yet challenging task, crucial for the diagnosing of many diseases. Current solutions rely on Convolutional Neural Networks and provide astonishing results. However, their performance is often measured only considering counting errors, which can lead to masked mistaken estimations; a low counting error can be obtained with a high but equal number of false positives and false negatives. Consequently, it is hard to determine which solution truly performs best. In this work, we investigate three general counting approaches that have been successfully adopted in the literature for counting several different categories of objects. Through an experimental evaluation over three public collections of microscopy images containing marked cells, we assess not only their counting performance compared to several state-of-the-art methods but also their ability to correctly localize the counted cells. We show that commonly adopted counting metrics do not always agree with the localization performance of the tested models, and thus we suggest integrating the proposed evaluation protocol when developing novel cell counting solutions.

Paper Citation

in Harvard Style

Ciampi L., Carrara F., Amato G. and Gennaro C. (2022). Counting or Localizing? Evaluating Cell Counting and Detection in Microscopy Images. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 887-897. DOI: 10.5220/0010923000003124

in Bibtex Style

@conference{visapp22,
author={Luca Ciampi and Fabio Carrara and Giuseppe Amato and Claudio Gennaro},
title={Counting or Localizing? Evaluating Cell Counting and Detection in Microscopy Images},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={887-897},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010923000003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Counting or Localizing? Evaluating Cell Counting and Detection in Microscopy Images
SN - 978-989-758-555-5
AU - Ciampi L.
AU - Carrara F.
AU - Amato G.
AU - Gennaro C.
PY - 2022
SP - 887
EP - 897
DO - 10.5220/0010923000003124
PB - SciTePress