Classification of Histopathological Images of Penile Cancer using DenseNet and Transfer Learning

Marcos Lauande, Amanda Teles, Leandro Lima da Silva, Caio Matos, Geraldo Braz Júnior, Anselmo Cardoso de Paiva, João Sousa de Almeida, Rui Oliveira, Rui Oliveira, Haissa Brito, Ana Nascimento, Ana Pestana, Ana Pestana, Ana Santos, Fernanda Lopes

2022

Abstract

Penile cancer is a rare tumor that accounts for 2% of cancer cases in men in Brazil. Histopathological analyzes are commonly used in its diagnosis, making it possible to assess the degree of the disease, its evolution, and its nature. About a decade ago, scientific works in the field of deep learning were developed to help pathologists make decisions quickly and reliably, opening up possibilities for new contributions to improve such a complex and time-consuming activity for these professionals. In this work, we present the development of a method that uses a DenseNet to diagnose penile cancer in histopathological images, and the construction of a dataset (via the Legal Amazon Penis Cancer Project) used to validate this method. In the experiments performed, an F1-Score of up to 97.39% and a sensitivity of up to 98.33% were achieved in this binary classification problem (normal or squamous cell carcinoma).

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Paper Citation


in Harvard Style

Lauande M., Teles A., Lima da Silva L., Matos C., Braz Júnior G., Cardoso de Paiva A., Sousa de Almeida J., Oliveira R., Brito H., Nascimento A., Pestana A., Santos A. and Lopes F. (2022). Classification of Histopathological Images of Penile Cancer using DenseNet and Transfer Learning. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-555-5, pages 976-983. DOI: 10.5220/0010893500003124


in Bibtex Style

@conference{visapp22,
author={Marcos Lauande and Amanda Teles and Leandro Lima da Silva and Caio Matos and Geraldo Braz Júnior and Anselmo Cardoso de Paiva and João Sousa de Almeida and Rui Oliveira and Haissa Brito and Ana Nascimento and Ana Pestana and Ana Santos and Fernanda Lopes},
title={Classification of Histopathological Images of Penile Cancer using DenseNet and Transfer Learning},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2022},
pages={976-983},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010893500003124},
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 - Volume 4: VISAPP,
TI - Classification of Histopathological Images of Penile Cancer using DenseNet and Transfer Learning
SN - 978-989-758-555-5
AU - Lauande M.
AU - Teles A.
AU - Lima da Silva L.
AU - Matos C.
AU - Braz Júnior G.
AU - Cardoso de Paiva A.
AU - Sousa de Almeida J.
AU - Oliveira R.
AU - Brito H.
AU - Nascimento A.
AU - Pestana A.
AU - Santos A.
AU - Lopes F.
PY - 2022
SP - 976
EP - 983
DO - 10.5220/0010893500003124