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Authors: Douglas Wender A. Isidoro 1 ; Cláudia M. Carneiro 2 ; Mariana T. Resende 2 ; Fátima N. S. Medeiros 3 ; Daniela M. Ushizima 4 and Andrea G. Campos Bianchi 1

Affiliations: 1 Computer Department, Universidade Federal de Ouro Preto, Ouro Preto, Brazil ; 2 Clinical Analysis Department, Universidade Federal de Ouro Preto, Ouro Preto, Brazil ; 3 Teleinformatics Engineering Department, Universidade Federal do Ceará, Ceará, Brazil ; 4 Lawrence Berkeley National Laboratory, Universidade de Berkeley, Califórnia, U.S.A.

Keyword(s): Pattern Recognition, Texture Features, Cervical Cell, Classification, Pap Smear.

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.

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Paper citation in several formats:
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; ISSN 2184-4321, SciTePress, pages 845-852. DOI: 10.5220/0009172208450852

@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},
issn={2184-4321},
}

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
IS - 2184-4321
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

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