Classification of Normal versus Leukemic Cells with Data Augmentation and Convolutional Neural Networks

José Elwyslan Maurício de Oliveira, Daniel Oliveira Dantas

2021

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.

Paper Citation

in Harvard Style

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, SciTePress, pages 685-692. DOI: 10.5220/0010257406850692

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Maurício de Oliveira J.
AU - Dantas D.
PY - 2021
SP - 685
EP - 692
DO - 10.5220/0010257406850692
PB - SciTePress