Brain Tumor Detection from Brain MRI Images with Deep Learning Methods

In this research, a deep learning model is proposed for brain tumor detection using brain MRI image collection. Three pre-trained convolutional neural networks are used as feature extractors. The obtained features are classified as brain tumors, normal, and tumorous using four different classifiers. Our proposed model has achieved a remarkable accuracy of 99.58% in its analysis, which is better than standard techniques. In addition, the proposed method has shown better performance than the convolutional neural network models used in the analysis.

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Publication Details

Published
2024-09-21
DOI
https://doi.org/10.1109/idap64064.2024.10710648
Citations
2
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.49
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article

Brain Tumor Detection from Brain MRI Images with Deep Learning Methods

Şükrü Aykat
2 citations
Brain Tumor Detection and Classification
0.49
article

Brain Tumor Detection from Brain MRI Images with Deep Learning Methods

Şükrü Aykat
article en
2 citations

Abstract

In this research, a deep learning model is proposed for brain tumor detection using brain MRI image collection. Three pre-trained convolutional neural networks are used as feature extractors. The obtained features are classified as brain tumors, normal, and tumorous using four different classifiers. Our proposed model has achieved a remarkable accuracy of 99.58% in its analysis, which is better than standard techniques. In addition, the proposed method has shown better performance than the convolutional neural network models used in the analysis.

Mardin Artuklu University (TR)
Openalex Percentile: Top 33%
Brain Tumor Detection and Classification
0.49
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Brain Tumor Detection from Brain MRI Images with Deep Learning Methods — Şükrü Aykat · (2024) | TGRS Research Map | TGRS