Optimal Classification of Brain Tumors in MRI Images Using Deep Learning Techniques

Subject Areas : Biomedical Engineering

Zohreh Arabi ¹ , Omid Mahdiyar ² , Mehdi Taghizadeh ³

1 - Department of Electrical Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran
2 - Department of Electrical Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran
3 - Department of Electrical Engineering, Kazerun Branch, Islamic Azad University, Kazerun, Iran

Received: 2023-09-06 Accepted : 2023-09-20 Published : 2023-09-25

Keywords: Medical Imaging, Brain tumors, Deep learning, MRI image, glioma, meningioma, pituitary,

Abstract :

Medical and biological imaging technologies provide valuable image information of the structure and function of an organ from the level of molecules to the whole body. The brain is the most complex organ in the body and is attracting increasing research attention with the rapid development of medical and biological imaging technologies. One of the most common brain diseases is the creation of abnormal tissue in brain cells, which leads to the formation of brain tumors. Since brain tumors are associated with a significant risk of death and the accurate and rapid prediction of this disease has a direct impact on the treatment process, therefore, in this research, a large number of brain tumor MRI imaging data was used to identify brain cancers and find a method. Deep learning techniques were used. Several deep learning models were used for automatic diagnosis, and the classification of three types of brain tumors, consisting of glioma, meningioma, and pituitary, was also done with these algorithms. Based on the results of the conducted tests, the best accuracy of the results obtained in this research was 96%, which was obtained by considering the ratio of 60% for training data and 40% for test data.

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