International Journal of

Automation and Smart Technology

Sahand Shahalinezhad1* and Mehdi Nooshyar2

1Bio Medical Engineering Dept., Urmia Institute of Higher Education, Urmia, Iran.
2Telecommunication Engineering, Electrical and Computer Engineering Dept., Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.

 

 

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ABSTRACT

A brain tumor is a collection or mass of abnormal cells in the brain, which cause an increase in intracranial pressure, which can cause brain damage and can be life threatening. Among all imaging techniques, MRI image analysis is a powerful tool for brain tumor diagnosis. In the past, segmentation algorithms were mainly used to diagnose this disease, but they are mostly problematic due to the complex structure of the brain and the presence of similar lesion areas. In this paper, we use these images to train the transfer learning (TL) model. We subsequently test this model with 5000 T2-weighted contrast-enhanced images with three types of brain disease. The results show that the TL model has high classification performance and accuracy in terms of brain tumor identification in medical images.


Keywords: Disease, Brain, Transfer Learning, MRI Images, Tumor detection.


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ARTICLE INFORMATION



Accepted: 2023-03-01
Available Online: 2023-03-01


Cite this article:

Shahalinezhad. S. and Nooshyar. N. (2023) Detection of Brain Tumor from MRI Images Base on Deep Learning technique Using TL Model. Int. j. autom. smart technol. https://doi.org/10.5875/ausmt.v13i1.2361

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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