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Authors: José Elwyslan Maurício de Oliveira and Daniel Oliveira Dantas

Affiliation: Departamento de Computação, Universidade Federal de Sergipe, São Cristóvão, SE, Brazil

Keyword(s): Leukemia Classification, Acute Lymphoblastic Leukemia.

Abstract: Acute lymphoblastic leukemia is the most common childhood leukemia. It is an aggressive cancer type and causes various health problems. Diagnosis depends on manual microscopic analysis of blood samples by expert hematologists and pathologists. To assist these professionals, image processing and pattern recognition techniques can be used. This work proposes simple modifications to standard neural network architectures to achieve high performance in the malignant leukocyte classification problem. The tested architectures were VGG16, VGG19 and Xception. Data augmentation was employed to balance the Training and Validation sets. Transformations such as mirroring, rotation, blurring, shearing, and addition of salt and pepper noise were used. The proposed method achieved an F1-score of 92.60%, the highest one when compared to other participants’ published results and eighth position when compared to the weighted F1-score provided by the competition leaderboard.

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Paper citation in several formats:
Maurício de Oliveira, J. and Dantas, D. (2021). Classification of Normal versus Leukemic Cells with Data Augmentation and Convolutional Neural Networks. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 685-692. DOI: 10.5220/0010257406850692

@conference{visapp21,
author={José Elwyslan {Maurício de Oliveira}. and Daniel Oliveira Dantas.},
title={Classification of Normal versus Leukemic Cells with Data Augmentation and Convolutional Neural Networks},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={685-692},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010257406850692},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Classification of Normal versus Leukemic Cells with Data Augmentation and Convolutional Neural Networks
SN - 978-989-758-488-6
IS - 2184-4321
AU - Maurício de Oliveira, J.
AU - Dantas, D.
PY - 2021
SP - 685
EP - 692
DO - 10.5220/0010257406850692
PB - SciTePress

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