Evaluation of the application of machine learning in the classification of brain tumors in MRI images

Saeed Yarmohammadi¹ Farzaneh Vali² Mahdis Parsafar³ Ali Samimi Fard⁴

1) PhD Student in Bioelectric Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran.
2) Bachelor of Clinical Medical Engineering, Ibn Sina University, Tehran, Iran.
3) PhD Student in Medical Engineering, Biomaterials, Islamic Azad University, Science and Research Branch, Tehran, Iran.
4) Master of Medical Engineering, Bioelectric, Islamic Azad University, Mashhad Branch, Khorasan Razavi, Iran.

IOI Code : XCCC-GAEEG
Publication : 10th International Conference on Innovative Technologies in Science, Engineering and Technology(tetsconf.com)
Abstract :
    Brain tumor is a life-threatening disease that affects millions of people. A brain tumor diagnosis and classification system is essential to ensure early diagnosis and classification of brain tumors. Because misdiagnosis leads to dire and fatal results, classification and segmentation techniques must be very careful when performing tumor classification. Therefore, the diagnosis of brain tumors and their classification are among the vital tasks for evaluating tumors and making a treatment decision accordingly. On the other hand, the impact of machine learning on our lives and society is increasing, and artificial intelligence may also play an important role in medical diagnosis and support for physicians and surgeons. Many machine learning methods have been developed to diagnose brain tumors. However, these methods, even if they provide good results, have not yet been used. Therefore, this issue remains an important research and still needs to be investigated.

Keywords : brain tumor magnetic resonance imaging segmentation machine learning algorithm