Advancements in Red Blood Cell Detection using Convolutional Neural Networks

František Kajánek, Ivan Cimrák

2020

Abstract

Extraction of data from video sequences of experiments is necessary for the acquisition of high volumes of data. The process requires Red Blood Cell detection to be of sufficient quality, so that the tracking algorithm has enough information for connecting frames and positions together. When holes occur in the detection, the tracking algorithm is only capable of fixing a certain amount of errors before it fails. In this work we iterate on existing frameworks and we attempt to improve upon the existing results of Convolutional Neural Network solutions.

Paper Citation

in Harvard Style

Kajánek F. and Cimrák I. (2020). Advancements in Red Blood Cell Detection using Convolutional Neural Networks. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS; ISBN 978-989-758-398-8, SciTePress, pages 206-211. DOI: 10.5220/0009165002060211

in Bibtex Style

@conference{bioinformatics20,
author={František Kajánek and Ivan Cimrák},
title={Advancements in Red Blood Cell Detection using Convolutional Neural Networks},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS},
year={2020},
pages={206-211},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009165002060211},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS
TI - Advancements in Red Blood Cell Detection using Convolutional Neural Networks
SN - 978-989-758-398-8
AU - Kajánek F.
AU - Cimrák I.
PY - 2020
SP - 206
EP - 211
DO - 10.5220/0009165002060211
PB - SciTePress