Automatic Classification of Cervical Cell Patches based on Non-geometric Characteristics

Douglas Wender A. Isidoro, Cláudia M. Carneiro, Mariana T. Resende, Fátima N. S. Medeiros, Daniela M. Ushizima, Andrea G. Campos Bianchi

2020

Abstract

This work presents a proposal for an efficient classification of cervical cells based on non-geometric characteristics extracted from nuclear regions of interested. This approach is based on the hypothesis that the nuclei store much of the information about the lesions in addition to their areas being more visible even with a high level of celular overlap, a common fact in the Pap smears images. Classification systems were used in two and three classes for a set of real images of the cervix from a supervised learning method. The results demonstrate high classification performance and high efficiency for applicability in realistic environments, both computational and biological.

Paper Citation

in Harvard Style

Isidoro D., Carneiro C., Resende M., Medeiros F., Ushizima D. and Bianchi A. (2020). Automatic Classification of Cervical Cell Patches based on Non-geometric Characteristics. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 845-852. DOI: 10.5220/0009172208450852

in Bibtex Style

@conference{visapp20,
author={Douglas Wender A. Isidoro and Cláudia M. Carneiro and Mariana T. Resende and Fátima N. S. Medeiros and Daniela M. Ushizima and Andrea G. Campos Bianchi},
title={Automatic Classification of Cervical Cell Patches based on Non-geometric Characteristics},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={845-852},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009172208450852},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Automatic Classification of Cervical Cell Patches based on Non-geometric Characteristics
SN - 978-989-758-402-2
AU - Isidoro D.
AU - Carneiro C.
AU - Resende M.
AU - Medeiros F.
AU - Ushizima D.
AU - Bianchi A.
PY - 2020
SP - 845
EP - 852
DO - 10.5220/0009172208450852
PB - SciTePress