Brain Tumor Classification using Machine and Transfer Learning

Iliass Zine-dine, Jamal Riffi, Khalid El Fazazi, Mohamed Adnane Mahraz, Hamid Tairi

2021

Abstract

Brain tumor classification is a controversial problem in computer-aided diagnosis (CAD). Conventionally, cancer diagnosis depends mainly on its early prediction. Accordingly, the improvement of technology and the rise of machines and deep learning facilitate the tasks of tumors’ detection and diagnosis while limiting human intervention. Transfer learning has been widely adopted in several applications due to its performance. In the present paper, we have combined VGG-16 and several classifiers for brain tumor classification. Indeed, after the fine-tuning step of VGG-16, we have fed the extracted features to the classifiers. The proposed approach has achieved efficient results and has outperformed several state-of-the-art studies in the topic of brain tumors in terms of precision (98.7%), recall 98.7, F1-score 98.7%.

Paper Citation

in Harvard Style

Zine-dine I., Riffi J., El Fazazi K., Mahraz M. and Tairi H. (2021). Brain Tumor Classification using Machine and Transfer Learning. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 566-571. DOI: 10.5220/0010762800003101

in Bibtex Style

@conference{bml21,
author={Iliass Zine-dine and Jamal Riffi and Khalid El Fazazi and Mohamed Adnane Mahraz and Hamid Tairi},
title={Brain Tumor Classification using Machine and Transfer Learning},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={566-571},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010762800003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Brain Tumor Classification using Machine and Transfer Learning
SN - 978-989-758-559-3
AU - Zine-dine I.
AU - Riffi J.
AU - El Fazazi K.
AU - Mahraz M.
AU - Tairi H.
PY - 2021
SP - 566
EP - 571
DO - 10.5220/0010762800003101